JP2006033225A - Image processing apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus capable of improving the loss of an edge in an image having a half tone and a change of in a thin line to a broken line. <P>SOLUTION: A window setting section 26 sets a window of 3×3 to a 256 gradation image. An edge strength detection section 27 detects edge strength in the window. A section 28 for determining the amount of fluctuation of dither thresholds obtains the amount of fluctuation of dither thresholds corresponding to the detected edge strength, based on information for indicating the relationship between the edge strength and the amount of fluctuation of dither thresholds. A binarization processor 25 obtains a new dither threshold, based on a dither threshold stored in a dither threshold storage 23 and the amount of fluctuation of dither thresholds determined by the section 28 for determining the amount of fluctuation of dither thresholds, and binarizes the 256 gradation image based on the new dither threshold and a 256 gradation image signal subjected to gamma correction by a gamma correction section 22. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus used in an image forming apparatus such as a color printer that executes an image forming process using an electrophotographic principle.

  In recent years, with the spread of computers and color printers, there have been increased opportunities for printing more color images by color printers in offices and homes.

  FIG. 12 is a diagram showing a usage form of a color printer. The color printer 1 is connected to a plurality of host computers 50 via an interface 53 such as IEEE1284 or a network such as a LAN (local area network) 51 and the Internet 52. The color printer 1 exchanges data such as print data and printer status information with the host computer 50.

  FIG. 13 is a configuration diagram showing the configuration of the color printer 1. In FIG. 13, a color printer 1 includes a controller unit 2 that interprets image data sent from a host computer 50 and generates a print image, and a printer engine 3 that forms print data on a recording medium using electrophotographic principles. Have.

  The controller unit 2 includes an interface unit 4 that controls data transmission and reception with the host computer 50, an interpreter unit 5 that interprets print data, a rasterizer unit 6 that forms a print image on a memory, and a compression that compresses the print image. And a decompressor 8 for decompressing the compressed print image.

  On the other hand, the printer engine 3 includes a laser driving device 9 that controls laser irradiation, a polygon mirror 10 that is mirror-finished into a polygon, a photoconductor 11 that forms an electronic latent image with a laser, and a plurality of cyan, magenta, yellow, and black. An intermediate transfer member 16 that transfers toner images formed by the developing units 12 and the developing units 12 and holds toner images of cyan (C), magenta (M), yellow (Y), and black (K); A paper cassette 17 for storing recording paper and a fixing device 19 for heating and fixing the toner image transferred onto the paper to the paper are provided.

  The processing operation of the color printer 1 having such a configuration will be described.

  The image data transmitted from the host computer 50 that has issued the print request is processed by the controller unit 2. That is, the image data is input to the interpreter unit 5 via the interface unit 4. The interpreter unit 5 interprets the image data and creates drawing data. The rasterizer unit 6 develops the print image on a band memory (not shown) obtained by dividing one page into a plurality of lines based on the created drawing data.

  Since the developed print image has a huge size, it is temporarily compressed by the compressor 7 and stored in a compression memory (not shown). When the storage of the print image image for one page is completed in the compression memory, the controller unit 2 causes the printer engine 3 to start a processing operation. The decompressor 8 sends the compressed print image image once stored to the printer engine 3 while decompressing it.

In the printer engine 3, the laser driving device 9 irradiates the polygon mirror 10 rotating at high speed while performing laser blinking control based on the data sent from the controller 2. The laser reflected light from the polygon mirror 10 is irradiated onto the photoconductor 11, whereby a latent image is formed on the photoconductor 11. At this time, the main scanning line of the image is formed by the rotation of the polygon mirror 10.

  The latent image formed on each photoconductor 11 is developed as a cyan, magenta, yellow, and black toner image by each developer 12. The toner image on each photoconductor 11 is once transferred to the intermediate transfer body 16.

  By the way, since each photoconductor 11 and each developing device 12 are arranged in series with respect to the driving direction of the intermediate transfer member 16, the intermediate transfer member 16 rotates cyan, magenta, yellow, It is possible to hold an image in which black toner is overlapped.

  The recording paper 13 is conveyed from the paper cassette 17 in synchronization with the movement of the intermediate transfer member 16. The toner image held on the intermediate transfer body 16 is transferred from the intermediate transfer body 16 onto the recording paper 13 by the transfer device 18 and then heated by the fixing device 19 to be fixed on the recording paper 13. As a result, a final output image is obtained.

  FIG. 14 is a configuration diagram illustrating a configuration of a conventional image processing apparatus. The image processing apparatus 6A shown in FIG. 14 is included in the rasterizer unit 6 in the controller unit 2 provided in the color printer 1 shown in FIG.

  The image processing apparatus 6A performs color conversion from RGB color to device color and binarization sent from the host computer 50, and includes a C signal processing unit 101C, an M signal processing unit 101M, and a Y signal processing unit 101Y. And a K signal processing unit 101K.

  The C signal processing unit 101C performs color conversion from RGB color to cyan (C) and binarization, and the M signal processing unit 101M, the Y signal processing unit 101Y, and the K signal processing unit 101K are also respectively provided. Magenta (M), yellow (Y), and black (K) are processed in the same manner as the C signal processing unit 101C.

  The C signal processing unit 101C includes a color conversion unit 20 that converts RGB color signals (hereinafter referred to as RGB signals) into cyan (C) color signals (hereinafter referred to as C signals), and a gamma for correcting engine output characteristics. A gamma table storage unit 21 that stores a correction table, a gamma correction unit 22 that performs gamma correction based on the gamma correction table, and a dither threshold matrix that stores a dither threshold matrix for halftoning a multi-valued image for each color of CMYK The storage unit 23 has a dither processing unit 24 that binarizes the image by comparing with the dither threshold matrix.

  The M signal processing unit 101M, the Y signal processing unit 101Y, and the K signal processing unit 101K also perform the same processing as the C signal processing unit 101C for magenta (M), yellow (Y), and black (K), respectively. Yes, it has the same configuration as the C signal processing unit 101C.

  Next, the operation of such an image processing apparatus 6A will be described. The RGB image data sent from the host computer 50 needs to be converted into CMYK data, which is the device color of the printer, and is therefore converted into CMYK data by the color conversion unit 20. Here, both RGB signals and CMYK signals are 256 gradation data having a level of 0 to 255.

In FIG. 14, the CMYK signal of 256 gradation data is shown as C (256), for example, to distinguish it from a binary CMYK signal to be described later, and for example, a C signal which is a cyan (C) color signal. . On the other hand, for a binary CMYK signal, for example, the C signal is illustrated as C (2). Furthermore, for an RGB signal of 256 gradation data, for example, an R signal that is a red (R) color signal is illustrated as R (256).

  By the way, since the correspondence between the RGB signal and the CMYK signal is highly non-linear, the typical color correspondence is represented by a lookup table. The color conversion unit 20 includes this lookup table, and performs conversion from RGB signals to CMYK signals by interpolating and obtaining representative points other than the representative points.

  Here, the CMYK four-color values are obtained using a lookup table. However, after the CMY three-color values are obtained using the lookup table, the CMYK four-color values are obtained by undercolor removal processing. Sometimes. There is also a method for obtaining CMY values using a masking matrix without using a lookup table.

  The CMYK signal that is the output of the color conversion unit 20 is further subjected to gamma correction by the gamma correction unit 22.

  FIG. 15 is a diagram showing characteristic information referred to by a gamma correction unit provided in a conventional image processing apparatus.

  The input signal (CMYK signal that is an output signal from the color converter 20) and the density of the output image have a non-linear relationship (output density characteristics) as shown in FIG. Varies depending on the toner and the material of the member used in the printing process.

  As described above, since the input signal and the density of the output image are in a non-linear relationship, it is necessary to adjust the output level of CMYK independently of color conversion in a printer engine using the principle of electrophotography. For this reason, the gamma table storage unit 21 has a gamma correction curve indicating a characteristic that is an inverse function of the output density characteristic shown in FIG. 15A, that is, a relationship between the input signal and the gamma correction level shown in FIG. Are stored in advance as a gamma correction table corresponding to each of CMYK.

  The gamma correction unit 22 that has received the CMYK signal from the color conversion unit 20 performs gamma correction on the CMYK signal with reference to each gamma correction table stored in the gamma table storage unit 21, thereby outputting CMYK output. I try to get linearity. The gamma-corrected CYK signal is input to the dither processing unit 24.

  Next, the dither processing unit 24 performs binarization for each plane of CMYK based on the YMCK signal from the gamma correction unit 22 and the dither threshold matrix stored in the dither matrix storage unit 21.

  FIG. 16 is a diagram illustrating an example of a dither threshold matrix. The dither matrix is an array of dither threshold values for each pixel level of the image.

  The dither processing unit 24 uses a CMYK in which the arrangement of dither thresholds is changed separately, and sets 1 for pixels that exceed the thresholds of the dither threshold matrix, while 0 for pixels that are lower than the thresholds. Get value data. The laser drive of the printer engine 3 is performed based on this binary data.

By the way, since the stability is not so good as the dot becomes smaller in electrophotography, the dither threshold matrix is arranged so that a plurality of pixels are arranged adjacent to each other as much as possible. Such binarization using the dither threshold matrix represents a gradation using a certain area of the area, and has a disadvantage that the gradation reproducibility is excellent but the resolution is not good.

  In order to compensate for such a defect, an apparatus is known in which it is determined whether or not an input pixel is a line segment edge region, and when it is determined that the input pixel is an edge image region, the image is binarized by a fixed threshold value ( For example, see Patent Document 1).

There is also known an apparatus that binarizes an image after performing edge enhancement on an input image signal (see, for example, Patent Document 2).
JP-A-63-256055 Japanese Patent Laid-Open No. 3-136468

  However, in the apparatus disclosed in the above (Patent Document 1), the precision of the fine line detection must be high. For this reason, in order to detect the fine line with high accuracy, the processing amount is increased and the fine line is highly accurate. There was a problem that the system for performing the detection would be complicated. Further, since binarization is performed with a fixed threshold value, there is a drawback that color combinations are limited in color.

  In addition, the apparatus disclosed in the above (Patent Document 2) can be realized with a relatively simple configuration to perform binarization processing by edge enhancement, but it emphasizes noise in an image. Therefore, image quality may be deteriorated in photographic images. Therefore, it is necessary to separately provide a circuit for determining whether the image is a character, a line drawing, or a photographic image, and to change the edge enhancement level for each region.

  SUMMARY An advantage of some aspects of the invention is that it provides an image processing apparatus that can improve edge loss of a halftone image and thin broken lines.

  In order to solve this problem, an image processing apparatus according to the present invention sets a window of n × n (n is an integer) for an M value image corresponding to an input M value image signal (M is an integer). Setting means; edge strength detection means for detecting edge strength within the window set by the window setting means; and dither threshold fluctuation amount determining means for obtaining a dither threshold fluctuation amount in accordance with the edge strength detected by the edge strength detection means. And a threshold value holding means for preliminarily holding a threshold value for converting the M-value image into an N-value image (N is an integer satisfying a relationship of M> N), and the threshold value and the dither threshold value variation determining means are obtained. A new threshold value is obtained based on the dither threshold fluctuation amount, and N-value conversion means for converting the M-value image into N-values based on the new threshold value and the M-value image signal is provided.

  The image processing apparatus of the present invention includes a window setting unit that sets n × n (n is an integer) window for an M-value image corresponding to an input M-value image signal (M is an integer); Edge intensity detecting means for detecting edge intensity within the window set by the window setting means, pixel value fluctuation amount determining means for obtaining a pixel value fluctuation amount according to the edge intensity detected by the edge intensity detecting means, and the M value Threshold value holding means for preliminarily holding a threshold value for converting an image into an N-value image (N is an integer satisfying the relationship of M> N), and the pixel obtained by the M-value image signal and the pixel value variation determining means A new pixel value is obtained based on the value fluctuation amount, and an N-value conversion unit that converts the M-value image into an N-value based on the new pixel value and the threshold value is provided.

Furthermore, the image processing apparatus according to the present invention is capable of M corresponding to the input M-value image signal (M is an integer).
Window setting means for setting n × n (n is an integer) window for the value image, detection means for detecting edge strength and edge direction within the window set by the window setting means, and detection means detecting First variation amount determining means for determining a dither threshold variation amount according to the edge strength, second variation amount determining means for determining a dither threshold variation amount corresponding to a pixel in the edge direction detected by the detection means, Threshold holding means for holding in advance a threshold for converting an M-value image into an N-value image (N is an integer that satisfies the relationship M> N), and the dither obtained by the threshold and the first variation determining means A new threshold value is obtained based on the threshold fluctuation amount and the dither threshold fluctuation amount obtained by the second fluctuation amount determining means, and the M-value image is converted into N values based on the new threshold value and the M-value image signal. It is obtained by a structure and a binarizing means.

  Furthermore, the image processing apparatus of the present invention includes a window setting unit that sets n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer), Detection means for detecting edge strength and edge direction in the window set by the window setting means, first fluctuation amount determination means for obtaining a pixel value fluctuation amount according to the edge strength detected by the detection means, and the detection means Second variation amount determining means for obtaining a pixel value variation amount corresponding to the pixel in the edge direction detected by, and for making the M-value image an N-value image (N is an integer satisfying a relationship of M> N) Based on a threshold value holding means for holding a threshold value in advance, the M value image signal, the pixel value fluctuation amount obtained by the first fluctuation amount determination means, and the pixel value fluctuation amount obtained by the second fluctuation amount determination means. To find a new pixel value Of the M value image based on the new pixel value and the threshold value is obtained by a structure having an N-value conversion means for N-value.

  According to the present invention, if a new threshold value is obtained based on the predetermined threshold value and the dither threshold fluctuation amount, and the M-value image is converted to N-values based on the new threshold value and the M-value image signal, halftone An effective effect is obtained that it is possible to improve the loss of the edge of the image and the broken line of the thin line.

  Further, according to the present invention, a new pixel value is obtained based on the M-value image signal and the pixel value fluctuation amount corresponding to the edge strength, and the M-value image is converted into an N value based on the new pixel value and a predetermined threshold value. If this is achieved, an effective effect is obtained that it is possible to improve the loss of the edge of the halftone image and the broken line.

  Further, according to the present invention, a new threshold value is obtained based on the predetermined threshold value, the dither threshold value fluctuation amount corresponding to the edge strength and the dither threshold value fluctuation amount corresponding to the edge direction, and the new threshold value and the M-value image signal are obtained. If an M-value image is converted to an N-value based on this, an effective effect is obtained in that it is possible to improve the loss of the edge of a halftone image and the generation of a broken line.

  Further, according to the present invention, a new pixel value is obtained based on the M-value image signal, the pixel value fluctuation amount corresponding to the edge intensity and the pixel value fluctuation amount corresponding to the edge direction, and the new pixel value and a predetermined threshold value are obtained. If the M-value image is converted into an N-value based on the above, an effective effect that an edge loss of a halftone image and a broken line of a thin line can be improved can be obtained.

According to the first aspect of the present invention, there is provided a window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an inputted M value image signal (M is an integer). Edge strength detecting means for detecting edge strength within the window set by the window setting means, dither threshold fluctuation amount determining means for obtaining a dither threshold fluctuation amount according to the edge strength detected by the edge strength detecting means, and an M-value image Based on threshold value holding means for preliminarily holding a threshold value for converting N into an N-value image (N is an integer that satisfies the relationship M> N), and the dither threshold value fluctuation amount obtained by the dither threshold value fluctuation amount determination means A new threshold value, and an N-value converting means for converting the M-value image into an N-value based on the new threshold value and the M-value image signal, and based on a predetermined threshold value and a dither threshold fluctuation amount New Since the threshold value is obtained and the M-value image is converted into an N-value based on the new threshold value and the M-value image signal, it is possible to improve the edge loss of the halftone image and the thin line broken line. Has an effect.

  According to a second aspect of the present invention, there is provided window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer). Edge strength detection means for detecting edge strength within the window set by the window setting means, pixel value fluctuation amount determination means for obtaining a pixel value fluctuation amount according to the edge strength detected by the edge strength detection means, and an M-value image Threshold value holding means for holding in advance a threshold value for converting an image into an N-value image (N is an integer satisfying the relationship of M> N), and a pixel value fluctuation amount obtained by an M-value image signal and a pixel value fluctuation amount determination means The image processing apparatus includes an N-value converting unit that obtains a new pixel value based on the N-value and converts the M-value image into an N-value based on the new pixel value and the threshold value. Based on the pixel value fluctuation amount Since a new pixel value is obtained and the M-value image is converted into an N-value based on the new pixel value and a predetermined threshold value, it is possible to improve the loss of the edge of the halftone image and the thin line broken line. Has the effect of being able to.

  According to a third aspect of the present invention, there is provided window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer). Detecting means for detecting edge strength and edge direction in the window set by the window setting means, first fluctuation amount determining means for obtaining a dither threshold fluctuation amount according to the edge intensity detected by the detecting means, and detecting means; A second variation determining means for obtaining a dither threshold variation corresponding to the detected pixel in the edge direction, and a threshold for converting the M-value image into an N-value image (N is an integer satisfying a relationship of M> N). Is obtained in advance based on the threshold value holding means for holding the threshold value, the dither threshold value fluctuation amount obtained by the first fluctuation amount determining means and the dither threshold value fluctuation amount obtained by the second fluctuation amount determining means. New threshold and M An image processing apparatus having an N-value conversion unit that converts an M-value image into an N-value based on an image signal, and a dither threshold fluctuation amount corresponding to a predetermined threshold value and edge strength and a dither threshold fluctuation amount corresponding to an edge direction Based on the above, a new threshold value is obtained, and the M-value image is converted to N-values based on the new threshold value and the M-value image signal. It has the effect of being able to.

  According to a fourth aspect of the present invention, there is provided window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer). Detecting means for detecting edge strength and edge direction in the window set by the window setting means, first fluctuation amount determining means for obtaining a pixel value fluctuation amount according to the edge strength detected by the detecting means, and detecting means; A second fluctuation amount determining means for obtaining a pixel value fluctuation amount corresponding to the detected pixel in the edge direction, and a threshold value for making the M-value image an N-value image (N is an integer satisfying a relationship of M> N). A new pixel value is obtained based on the threshold value holding means held in advance, the M-value image signal, the pixel value fluctuation amount obtained by the first fluctuation amount determination means, and the pixel value fluctuation amount obtained by the second fluctuation amount determination means. Based on this new pixel value and threshold. And an N-value converting means for converting the M-value image into an N-value, based on the M-value image signal, the pixel value fluctuation amount corresponding to the edge intensity, and the pixel value fluctuation amount corresponding to the edge direction. Since a new pixel value is obtained and the M-value image is converted into an N-value based on the new pixel value and a predetermined threshold value, it is possible to improve the loss of the edge of the halftone image and the broken line of the thin line. Has the effect of being able to.

  Hereinafter, the best mode for carrying out the present invention will be described more specifically with reference to the drawings. Here, in the accompanying drawings, the same reference numerals are given to the same members, and duplicate descriptions are omitted. In addition, since description here is the best form by which this invention is implemented, this invention is not limited to the said form.

(Embodiment 1)
FIG. 1 is a block diagram showing a configuration of an image processing apparatus according to Embodiment 1 of the present invention, FIG. 2 is a diagram showing an example of an image in which a window is set, and FIG. 3 is a relationship between edge strength and dither threshold fluctuation amount. FIG. 4 is a diagram showing an example of an array of dither threshold values for the cyan plane, and an example of a diagonal line whose line pixel level is 2 dots wide, and FIG. 5 shows a line drawing reproduced based on the contents shown in FIG. FIG. 6 is a diagram showing an example of an array of dither threshold values after the dither threshold value variation process is performed on the contents shown in FIG. 4, and FIG. 7 is a line drawing reproduced based on the contents shown in FIG. FIG.

  An image processing apparatus 60 shown in FIG. 1 is included in the rasterizer unit 6 provided in the conventional color printer 1 shown in FIG. 13, and includes a C signal processing unit 102C, an M signal processing unit 102M, and a Y signal. A signal processing unit 102 having a processing unit 102Y and a K signal processing unit 102K is provided.

  The C signal processing unit 102C, the M signal processing unit 102M, the Y signal processing unit 102Y, and the K signal processing unit 102K are respectively the cyan (C), magenta (M), yellow (Y), and black (K) planes. Creates an engine output image. Since each of these signal processing units has the same configuration and operation, in the following description, the C signal processing unit 102C that outputs a cyan plane will be described.

  The C signal processing unit 102C includes a color conversion unit 20, a gamma table storage unit 21, a gamma correction unit 22, a dither threshold storage unit 23, a binarization processing unit 25, a window setting unit 26, an edge intensity detection unit 27, and a dither threshold. A variation determining unit 28 is provided.

  The color conversion unit 20 converts the RGB color signal (RGB signal) into a cyan (C) color signal (referred to as a C signal). Since the correspondence between the RGB signals and the CMYK signals is highly non-linear, the color conversion unit 20 includes a look-up table that represents the correspondence between representative colors.

  The gamma table storage unit 21 stores a gamma correction table for correcting engine output characteristics. The gamma correction unit 22 performs gamma correction based on the gamma correction table.

  The dither threshold storage unit (threshold holding means) 23 converts an M-value image corresponding to an input M-value image, for example, a 256-gradation image corresponding to an image signal of 256 gradations into an N-value image (N is a relationship of M> N). For example, a threshold value (dither threshold value) for conversion into a binary image is held in advance.

  The window setting unit (window setting means) 26 sets an n × n (n is an integer), for example, 3 × 3 window for an M-value image (M is an integer), for example, a 256 gradation image.

  The edge strength detection unit (edge strength detection means) 27 detects the edge strength within the window set by the window setting unit 26.

  The dither threshold fluctuation determining unit (dither threshold fluctuation determining unit) 28 determines the dither threshold fluctuation according to the edge strength detected by the edge strength detection unit 27. A storage unit (not shown) for storing information representing the relationship is provided, and the dither threshold fluctuation amount corresponding to the detected edge strength is obtained by referring to the storage content of the storage unit.

The binarization processing unit (N-value conversion unit) 25 is based on the threshold value (dither threshold value) stored in the dither threshold value storage unit 23 and the dither threshold value variation amount determined by the dither threshold value variation amount determination unit 28. A new threshold value (new dither threshold value) is obtained, the new dither threshold value, and the gamma correction unit 2
The 256 gradation image is converted to N-value (binarization) based on the 256 gradation image signal that has been gamma-corrected by 2.

  Next, the processing operation of the image processing apparatus 60 will be described.

  The RGB image data (256 gradation image data) sent from the host computer 50 is converted into a cyan color signal (C signal), that is, a 256 gradation C signal by the color converter 20. At this time, the color conversion unit 20 performs conversion from the RGB signal to the C signal by referring to a lookup table for representative colors, and interpolates and obtains representative points other than the representative points from the RGB signals. Conversion to C signal is performed.

  In the following description, in order to distinguish between a 256-level C signal and a binary C signal, the 256-level C signal is referred to as a C (256) signal, while the binary C signal is C (2) signal. In addition, a 256-tone C signal subjected to gamma correction, which will be described later, is referred to as a C ′ (256) signal.

  In FIG. 1, the RGB signal (image data) with 256 gradations is shown as R (256), G (256), and B (256), respectively. The CMYK signal with 256 gradations is 256, for example. The C signal of gradation is shown as C (256), the C signal of 256 gradation after gamma correction described later is shown as C ′ (256), and the binary C signal is shown as C (2). To do.

  The C (256) signal that is the output of the color conversion unit 20 is input to the gamma correction unit 22 and the window setting unit 26.

  The gamma correction unit 22 performs gamma correction on the input C (256) signal based on the gamma correction table stored in the gamma table storage unit 21. That is, the gamma correction unit 22 obtains the linearity of the output by acquiring the correction value for the C (256) signal from the gamma correction table of the gamma table storage unit 21. As a result, a gamma-corrected C ′ (256) signal is obtained.

  On the other hand, the window setting unit 26 to which the color-converted C (256) signal is input sets an n × n window centered on the pixel of interest with respect to the C (256) signal (input image signal). . Here, assume that n = 3 and 3 × 3 window setting is performed.

  FIG. 2 shows an example of an image in which a 3 × 3 window is set. The image in this window is composed of 3 × 3 pixels centering on the current pixel of interest indicated by hatched hatching. For example, the pixel of interest g11 is composed of pixels g00, g01, g02, g10, g12, g20, g21, and g22.

  Subsequently, the edge strength detection unit 27 obtains the edge strength Es of the 3 × 3 window set by the window setting unit 26. The edge strength Es is indicated by the minimum value of the difference from the peripheral pixel to the target pixel, and can be obtained by calculating the expressions (Equation 1) and (Equation 2).

  However, min (*) is a function for obtaining the minimum value.

  The edge strength Es obtained in this way is input to the dither threshold value variation determining means 28.

  The dither threshold fluctuation amount determining means 28 uses the dither threshold fluctuation amount Ds corresponding to the edge strength Es as information indicating the relationship between the edge strength Es and the dither threshold fluctuation amount Ds stored in the storage unit (not shown). To convert the input edge strength Es into a dither threshold fluctuation amount Ds. The dither threshold fluctuation amount Ds thus converted is passed to the binarization processing unit 25.

  Here, the relationship between the edge strength Es and the dither threshold fluctuation amount Ds can be expressed as a table as shown in FIG. The table shown in FIG. 3 shows that when the edge strength Es is small, the dither threshold fluctuation amount Ds is smaller or the dither threshold fluctuation amount Ds becomes 0, and the dither threshold fluctuation amount Ds becomes larger as the edge strength Es becomes stronger. It is set to be large.

  Such a table is used for converting the edge strength Es in the range of 0 to 255 into the dither threshold fluctuation amount Ds having a value of 0.0 to 1.0. Is stored in a storage unit (not shown).

  The binarization processing unit 25 passed the dither threshold fluctuation amount Ds first acquires the dither threshold T from the storage contents of the dither threshold storage unit 23. As the dither threshold T, a value arranged at a position corresponding to the position of the pixel of interest is acquired. With respect to the dither threshold value T, the dither threshold value is changed using the dither threshold value fluctuation amount Ds.

  Specifically, when the dither threshold value after the change is T ′, the dither threshold value T ′ can be obtained by calculating the equation (Equation 3).

  As can be seen from the equation (Equation 3), the dither threshold T ′ that varies according to the value of the dither threshold variation Ds is smaller than the normal dither threshold T.

  By the way, the binarization processing unit 25 compares the pixel level based on the C ′ (256) signal after gamma correction and the dither threshold value T ′ after fluctuation, and as a result of the comparison, based on the C ′ (256) signal. When the relationship of pixel level ≧ dither threshold value T ′ is established, the output is turned on. On the other hand, when the relationship of pixel level <dither threshold value T ′ based on the C ′ (256) signal is established, the binary output is turned off. obtain.

  When binarization is performed in this way, the portion where the edge strength Es is stronger becomes larger within the range of the dither threshold fluctuation amount Ds between 0.0 and 1.0 (see FIG. 3). Along with this, the dither threshold T ′ becomes smaller (see Equation 3), so that the image is likely to appear.

FIG. 4 shows an example of an array of dither thresholds for a cyan plane and a two-dot wide diagonal line with a line pixel level (cyan monochromatic level) of 60. In FIG. 4, the number of each cell corresponding to each pixel indicates a dither threshold, and the pixels surrounded by a thick line indicate the pixels constituting the 2-dot width line.

  When the dither threshold T is applied as it is and binarized, a line image as shown in FIG. 5 is reproduced, so that the line is represented by discrete dots and appears as a broken line.

  FIG. 6 shows a state in which the dither threshold values T ′ after the dither threshold value variation processing are arranged. As can be seen from FIG. 6, since the edge strength Es appears strongly in the portion where the line exists (the pixel portion surrounded by the thick line), the value of the dither threshold fluctuation amount Ds increases as described above, and as a result, The dither threshold level of only that portion is lowered.

  In this embodiment, the new dither threshold T ′ is compared with the pixel level (pixel value of the 256 gradation image) based on the C ′ (256) signal after gamma correction, and 2 based on the comparison result. However, the present invention is not limited to this, and may be as follows.

  That is, the pixel value fluctuation amount is obtained according to the detected edge intensity for the target pixel, and a new pixel value is obtained based on the pixel value fluctuation amount and the pixel value of the target pixel. The pixel value may be compared with a predetermined dither threshold value and binarized based on the comparison result.

  In this case, in FIG. 1, the dither threshold value fluctuation amount determination unit 28 is a pixel value fluctuation amount determination unit that obtains the pixel value fluctuation amount Ds in accordance with the edge strength Es detected by the edge strength detection unit (edge strength detection unit) 27. It shall have a function.

  In addition, the binarization processing unit 25 is a pixel value variation determined by the 256 gradation image signal (M-value image signal) after the gamma correction and the pixel value variation determination unit (dither threshold variation determination unit 28). A new pixel value is obtained based on Ds, and the 256 gradation image is binarized (N-valued) based on the new pixel value and the dither threshold value T acquired from the stored contents of the dither threshold value storage unit 23. Thereby, it is possible to improve the loss of the edge of the halftone image and the broken line of the thin line.

  Further, in this embodiment, one dither threshold is changed for one pixel and binarized, but the present invention is not limited to this, and a plurality of dithers for one pixel. A threshold value may be provided, and each dither threshold value may be varied to obtain an n-value value having n gradation values.

  In this embodiment, the image processing apparatus can be realized by using dedicated hardware. However, the image processing apparatus is configured by a general CPU (central processing unit) and a storage medium such as a ROM or a RAM. It is also possible to realize the same processing as that of the image processing apparatus.

  In this case, the function of the color signal processing unit is realized, a program indicating the processing procedure of the processing is stored in, for example, a ROM, and the CPU loads the program from the ROM to the main storage device (RAM) and executes it. To do.

  Furthermore, in this embodiment, the printer engine is described as a color printer using electrophotography, but the printer engine does not necessarily have to use electrophotography.

As described above, according to the image processing apparatus of the present embodiment, a new dither threshold (new threshold) T ′ is obtained based on the dither threshold (predetermined threshold) T and the dither threshold fluctuation amount Ds, and this new Based on the dither threshold T ′ and the gamma-corrected 256 gradation (256 values) image signal (256 gradation YMCK signal), the 256 gradation image is binarized (N value). It is possible to improve the loss of the edge of the tone image and the broken line.

(Embodiment 2)
8 is a block diagram showing the configuration of the image processing apparatus according to the second embodiment of the present invention, FIG. 9 is a diagram showing the relationship between the edge strength and the fluctuation adjustment amount, and FIG. 10 is a diagram for explaining the fluctuation adjustment amount. 11 is a diagram showing the relationship between the edge strength and the current fluctuation amount.

  The image processing apparatus according to this embodiment has basically the same function as the image processing apparatus according to the first embodiment, but the process for changing the dither threshold using the dither threshold fluctuation amount is different. .

  Also in this embodiment, in order to distinguish between the 256-level C signal and the binary C signal, the 256-level C signal is expressed as a C (256) signal, while the binary C signal is C (2) signal. In addition, a 256-tone C signal subjected to gamma correction, which will be described later, is referred to as a C ′ (256) signal.

  In FIG. 8, RGB signals (image data) with 256 gradations are respectively shown as R (256), G (256), and B (256), and for each CMYK signal, for example, 256 gradations. The C signal of C is shown as C (256), and a C signal of 256 gradations, which will be described later, is expressed as C ′ (256), and the binary C signal is shown as C (2).

  An image processing apparatus 600 shown in FIG. 8 is included in the rasterizer unit 6 provided in the conventional color printer 1 shown in FIG. 13, and includes a color signal processing unit 103 and a threshold variation determining unit 104. ing.

  The threshold fluctuation amount determination unit 104 includes a brightness conversion unit 30, a window setting unit 31, an edge strength detection unit 32, an edge direction detection unit 33, a fluctuation adjustment amount determination unit 34, and a current fluctuation amount determination unit 35.

  The lightness conversion unit 30 obtains lightness from the RGB input signals.

  The window setting unit (window setting means) 31 sets a window of n × n (n is an integer), for example, 3 × 3, for the M-value image corresponding to the input M-value image signal (M is an integer).

  The edge strength detection unit (detection means) 32 detects the edge strength in the window set by the window setting unit 31.

  The edge direction detection unit (detection means) 33 detects the edge direction in the window set by the window setting unit 31.

  The fluctuation adjustment amount determination unit (second variation amount determination unit) 34 applies the pixel in the edge direction based on the edge strength obtained by the edge strength detection unit 32 and the edge direction obtained by the edge direction detection unit 33. A corresponding dither threshold fluctuation amount (a fluctuation adjustment amount described later) is obtained. The fluctuation adjustment amount determination unit 34 includes a storage unit (not shown) that stores information (fluctuation adjustment amount conversion table) representing the relationship between the edge strength and the fluctuation adjustment amount. Refer to this table. The variation adjustment amount for the pixels in the edge direction is obtained.

  The current variation determining unit (first variation determining unit) 35 calculates a dither threshold variation (a current variation described later) according to the edge strength obtained by the edge strength detector 32. Further, the current variation determination unit 35 includes a storage unit (not shown) that stores information representing the relationship between the edge strength and the current variation amount. The current fluctuation amount corresponding to the edge strength is obtained.

  On the other hand, the color signal processing unit 103 includes a signal processing unit 103 including a C signal processing unit 103C, an M signal processing unit 103M, a Y signal processing unit 103Y, and a K signal processing unit 102K. The engine output image of each plane of (C), magenta (M), yellow (Y), and black (K) is created. Since these signal processing units have the same configuration and operation, in the following description, the C signal processing unit 102C that outputs a cyan plane will be described.

  The C signal processing unit 103 </ b> C includes a color conversion unit 20, a gamma table storage unit 21, a gamma correction unit 22, a dither threshold storage unit 23, and a binarization processing unit 36. Of these components, the components other than the binarization processor 36 have the same functions as the components 20, 21, 22, 23 of the C signal processor 102C shown in FIG. The description is omitted here.

  The binarization processing unit (N-value conversion unit) 36 includes a threshold value (dither threshold value) stored in the dither threshold value storage unit 23, a dither threshold value variation amount obtained by the current variation amount determination unit 35, and a variation adjustment amount. A new threshold value (new dither threshold value) is obtained based on the dither threshold fluctuation amount obtained by the determination unit 34, and based on the new dither threshold value and the 256 tone image signal that has been gamma corrected by the gamma correction unit 22. Then, the 256 gradation image is converted to N-value (binarization).

  Next, the processing operation of the image processing apparatus 600 will be described.

  The lightness conversion unit 30 calculates the lightness signal Y by calculating the equation of Y = 0.3R + 0.6G + 0.1B based on the RGB input signal, and passes this lightness signal Y to the window setting unit 31.

  Next, the window setting unit 31 sets an n × n window centered on the pixel of interest for the lightness signal Y. Here, it is assumed that n = 3 and 3 × 3 window setting is performed (see FIG. 2). The window set by the window setting unit 31 (the window for the lightness signal Y) is input to the edge enhancement detection unit 32 and the edge direction detection unit 33.

  Subsequently, the edge strength detection unit 32 obtains the edge strength Es of the 3 × 3 window (see FIG. 2) set for the lightness signal Y. This edge strength Es is obtained by the maximum value of the difference from the surrounding pixels to the target pixel. In this embodiment, since the edge intensity Es is detected with respect to the brightness, the edge intensity Es can be obtained by calculating the expressions (Equation 4) and (Equation 5).

  However, Max (*) is a function for obtaining the maximum value.

  The edge strength Es obtained in this way is input to the fluctuation adjustment amount determination unit 34 and the current fluctuation amount determination unit 35.

  The edge direction detection unit 33 detects the direction of the edge formed by the pixels in the 3 × 3 window set for the lightness signal Y.

  The edge direction Ed is obtained by performing extraction in four directions of horizontal (Edh), vertical (Edv), right-up diagonal (Edr), and left-up diagonal (Edl), and the edge strength detection unit 32 detects the edge strength. It is obtained as a direction perpendicular to the position of the pixel that gives gMax when it is performed (result obtained by calculating Expression 4).

  For example, in the example shown in FIG. 2, when the pixel that gives gMax to the pixel of interest g11 is the lower right pixel g22, the edge direction Ed is a right-upward diagonal (Edr) that is perpendicular to the pixel direction. When the pixel giving gMax to the pixel of interest g11 is g12 on the right side, the edge direction Ed is vertical (Edv).

  The edge direction Ed obtained by the edge direction detection unit 33 is input to the fluctuation adjustment amount determination unit 34.

  The variation adjustment amount determination unit 34 obtains the variation adjustment amount Dadj from the edge strength Es and temporarily stores it in the edge direction Ed already received from the edge enhancement detection unit 32.

  FIG. 9 shows characteristics (a graph of the fluctuation adjustment amount conversion table) representing the relationship between the edge strength Es and the fluctuation adjustment amount (dither threshold fluctuation amount) Dadj. The characteristic information as shown in FIG. 9 is stored in a storage unit (not shown) of the conversion adjustment amount determination unit 34.

  As can be seen from FIG. 9, when the edge strength Es is small, the variation adjustment amount Dadj is smaller or the variation adjustment amount Dadj becomes 0, and the variation adjustment amount Dadj becomes larger as the edge strength Es becomes stronger. Is set to Such a table is used for converting the edge enhancement Es in the range of 0 to 255 into the fluctuation adjustment amount Dadj of 0.0 to 1.0.

  The fluctuation adjustment amount determination unit 34 sets the fluctuation adjustment amount Dadj as to the right direction of the pixel of interest when the edge direction is horizontal (Edh), and as the lower direction when the edge direction is vertical (Edv). In the case of diagonally upward (Edr), addition and storage are performed for the lower left direction, and in the case of diagonally upward left (Edl), the addition is performed for the lower right direction.

  Here, a method of obtaining the fluctuation adjustment amount Dadj by the fluctuation adjustment amount determination unit 34 will be specifically described with reference to FIG.

  First, as described above, the window setting unit 31 sets a 3 × 3 window surrounded by a thick line with the pixel A as the target pixel, as shown in FIG. The edge strength detection unit 32 detects edge strength in the window, and the edge direction detection unit 33 detects edge direction in the window.

The variation adjustment amount determination unit 34 obtains a variation adjustment amount corresponding to the pixel in the edge direction based on the edge strength and the edge direction. Next, when the obtained variation adjustment amount is Dadj0 and the edge direction Ed is vertical (Edv), the variation adjustment amount determination unit 34 determines the direction of the pixel C positioned below the pixel A of interest. The fluctuation adjustment amount Dadj0 is stored.

  Subsequently, the pixel of interest moves from the pixel A to the pixel B, and as shown in FIG. 10B, the window is set at a position moved to the right as compared with the position of the window shown in FIG. In such a case, the fluctuation adjustment amount determination unit 34 determines that the fluctuation adjustment amount Dadj1 is again a pixel that is at the lower left of the pixel of interest B when the edge direction Ed is diagonally upward (Edr) with the fluctuation adjustment amount Dadj1. Although it is stored at the position C, it is added to the previously stored variation adjustment amount Dadj0 and stored.

  At this time, since the fluctuation adjustment amount is a value between 0.0 and 1.0, if the addition result exceeds 1.0, it is clipped to 1.0 and stored. In the following description, it is assumed that the amount of fluctuation adjustment after the addition is stored is Da (0.0 ≦ Da ≦ 1.0).

  Meanwhile, the current fluctuation amount determination unit 35 that has received the edge enhancement Es from the edge enhancement detection unit 32 converts the edge enhancement Es into a current fluctuation amount Ds. The relationship between the edge strength Es and the current fluctuation amount Ds can be expressed as a table as shown in FIG. Information indicating the relationship as shown in FIG. 11 is stored in a storage unit (not shown) of the current variation determining unit 35.

  This table is set so that the current fluctuation amount Ds is smaller or the current fluctuation amount Ds becomes 0 when the edge strength Es is small, and the current fluctuation amount Ds becomes larger as the edge strength Es becomes stronger. ing. Such a table is used for converting the edge strength Es in the range of 0 to 255 into the value of the current fluctuation amount Ds of 0.0 to 1.0.

  The current variation amount Ds and the previously obtained variation adjustment amount Da are passed to the color signal processing unit 103. For example, when the target pixel moves to the pixel C in the window shown in FIG. 10C, the current variation amount Ds obtained corresponding to the position of the pixel C and the variation stored corresponding to the position of the pixel C. The adjustment amount Da is passed.

  The color signal processing unit 103 to which the current fluctuation amount Ds and the fluctuation adjustment amount Da are passed in this way will be described. Here, processing in the case of converting RGB image data into dian (C) color signals will be described.

  The RGB image data (256 gradation image data) sent from the host computer 50 is converted into a cyan color signal, that is, a C (256) signal by the color conversion unit 20. At this time, the color conversion unit 20 performs conversion from the RGB signal to the C signal by referring to a lookup table for representative colors, and interpolates and obtains representative points other than the representative points from the RGB signals. Conversion to C (256) signal is performed. The C (265) signal that has been color-converted in this way is input to the gamma correction unit 22.

  The gamma correction unit 22 performs gamma correction on the input C (256) signal based on the gamma correction table stored in the gamma table storage unit 21. That is, the gamma correction unit 22 obtains the linearity of the output by acquiring the correction value for the C (256) signal from the gamma correction table of the gamma table storage unit 21. As a result, a gamma-corrected C ′ (256) signal is obtained. The C ′ (256) signal thus obtained is input to the binarization processing unit 36.

  The binarization processing unit 36 is based on the value of the color signal after the gamma correction (C ′ (256) signal) from the gamma correction unit 22 and the current variation amount Ds and variation adjustment amount Da from the threshold variation determination unit 104. Then, binarization processing is executed.

  The binarization processing unit first acquires a dither threshold T stored in the dither threshold storage unit 23. As the dither threshold T, a value arranged at a position corresponding to the position information of the pixel of interest is acquired. With respect to the dither threshold value, the threshold value is varied using the dither threshold value variation amount (current variation amount Ds and variation adjustment amount Da).

  Specifically, when the dither threshold value after change is T ′, the dither threshold value T ′ can be obtained by calculating the equation (Equation 6).

  As can be seen from the equation (Equation 6), the dither threshold value T ′ that varies according to each value of the current variation amount Ds and the variation adjustment amount Da is smaller than the normal dither threshold value T. The fluctuation adjustment amount Da approaches a value of 1.0 when particularly high-strength edges continue in the same direction, but approaches 0 when the edge strength is weak or the edge directions are not continuous. Therefore, when the fluctuation adjustment amount Da is a value that approaches 0, the change amount ((1-Ds) ^ Da) of the dither threshold decreases.

  By the way, the binarization processing unit 36 compares the pixel level based on the C ′ (256) signal on which the gamma correction has been performed with the dither threshold value T ′ after the change, and as a result of the comparison, the C ′ (256) signal is obtained. When the relationship of ≧ dither threshold value T ′ is established, the output is turned on, and when the relationship of C ′ (256) signal <dither threshold value T ′ is established, the binary output is obtained.

  When binarization is performed in this way, in the portion where the edge strength Es is stronger, the dither threshold value T is greatly decreased, and as a result, the dither threshold value T ′ becomes smaller, so that pixels are likely to appear. Further, when the edges continue in the same direction, the dither threshold value T is greatly decreased, and as a result, the dither threshold value T ′ is decreased, so that pixels are particularly likely to appear on a straight line.

  In this embodiment, the pixel variation of the edge is improved by changing the dither threshold by using the current change amount Ds and the change adjustment amount Da that are the outputs of the threshold change amount determination unit 104. The present invention is not limited to this. After the current fluctuation amount Ds and the fluctuation adjustment amount Da are applied to the pixel level, the pixel level is compared with the dither threshold T, and binarization is performed based on the comparison result. By doing so, pixel reproduction can be improved.

  Specifically, in FIG. 8, the current fluctuation amount determination unit (first fluctuation amount determination unit) 35 determines the pixel value fluctuation amount (current fluctuation amount) according to the edge strength detected by the edge strength detection unit (detection unit) 32. A variation adjustment amount determination unit (second variation amount determination unit) 34 has a function of obtaining an amount Ds, and a pixel value variation amount corresponding to the pixel in the edge direction detected by the edge direction detection unit (detection unit) 33 (Variation adjustment amount) It shall have a function which calculates | requires Da.

The binarization processing unit 36 uses the 256-gradation image signal (M-value image signal) after gamma correction and the pixel variation Ds and variation obtained by the current variation determination unit (first variation determination unit) 35. A new pixel value is obtained based on the pixel variation amount Da obtained by the adjustment amount determination unit (second variation amount determination means) 34, and the dither threshold value T acquired from the new pixel value and the stored contents of the dither threshold value storage unit 23. Based on the above, the 256 gradation image is converted to N-value.

  Here, the new pixel value G ′ after the change with respect to the pixel value G can be obtained by calculating the equation (Equation 7).

  Then, the binarization processing unit 36 compares the pixel value G ′ obtained by calculating the equation (Equation 7) and the dither threshold T, and as a result of the comparison, the pixel value G ′ ≧ the dither threshold T is satisfied. A binary output is obtained that is ON when the relationship is established, and is OFF when the relationship of pixel value G ′ <dither threshold T ′ is established.

  Further, in this embodiment, one dither threshold is changed for one pixel and binarized, but the present invention is not limited to this, and a plurality of dithers for one pixel. A threshold value may be provided, and each dither threshold value may be varied to obtain an n-value value having n gradation values.

  Furthermore, in this embodiment, the image processing apparatus can be realized using dedicated hardware, but is configured by a general CPU (central processing unit) and a storage device such as a ROM or RAM. It is also possible to realize the same processing.

  In this case, the functions of the color signal processing unit and the threshold variation determining unit are realized, and a program indicating the processing procedure of the processing is stored in, for example, a ROM, and the CPU stores the program from the ROM in the main memory (RAM). ) To be executed.

  Furthermore, in this embodiment, the printer engine is described as a color printer using electrophotography, but the printer engine does not necessarily have to use electrophotography.

  As described above, according to the image processing apparatus of the present embodiment, the new dither threshold (new threshold) T ′ is set based on the dither threshold (predetermined threshold) T, the current fluctuation amount Ds, and the fluctuation adjustment amount Da. Based on this new dither threshold T ′ and the gamma-corrected 256 gradation (256 values) image signal (256 gradation YMCK signal), the 256 gradation image is binarized (N value). Therefore, it is possible to improve the loss of the edge of the halftone image and the broken line.

  Further, according to the image processing apparatus of the present embodiment, a new pixel G ′ is obtained based on the pixel value G of the pixel of interest, the current fluctuation amount Ds, and the fluctuation adjustment amount Da, and the new dither threshold G ′ and gamma correction. Based on the 256-gradation (256-value) image signal (256-gradation YMCK signal), the 256-gradation image is binarized (N-value), so that the edge of the halftone image is missing. And the thin line can be improved.

1 is a configuration diagram showing a configuration of an image processing apparatus according to a first embodiment of the present invention. The figure which shows an example of the image where the window is set Diagram showing the relationship between edge strength and dither threshold variation The figure which shows an example of the arrangement | sequence of the dither threshold value with respect to a cyan plane, and the oblique line whose line pixel level is 2 dot width The figure which shows the mode of the line drawing reproduced based on the content shown in FIG. The figure which shows the mode after performing the dither threshold value variation process with respect to the content shown in FIG. The figure which shows the mode of the line drawing reproduced based on the content shown in FIG. The block diagram which shows the structure of the image processing apparatus which is Embodiment 2 of this invention. Diagram showing the relationship between edge strength and variation adjustment amount Diagram explaining the amount of fluctuation adjustment Diagram showing the relationship between edge strength and current variation A diagram showing how the color printer is used Configuration diagram showing the configuration of a color printer The block diagram which shows the structure of the conventional image processing apparatus The figure which shows the characteristic information referred by the gamma correction part provided in the conventional image processing apparatus Figure showing an example of a dither threshold matrix

Explanation of symbols

20 color conversion unit 21 gamma table storage unit 22 gamma correction unit 23 dither threshold storage unit (threshold holding means)
25, 36 Binary processing unit (N-value conversion means)
26, 31 Window setting section (window setting means)
27 Edge strength detection unit (edge strength detection means)
28 Dither threshold variation determining unit (dither threshold variation determining means)
30 lightness conversion unit 32 edge strength detection unit (detection means)
33 Edge direction detection unit (detection means)
34. Fluctuation adjustment amount determination unit (second variation amount determination means)
35 Current variation determining unit (first variation determining means)
60,600 Image processing apparatus 102, 103 Color signal processing unit 102C, 103C Cyan (C) signal processing unit 102M, 103M Magenta (M) signal processing unit 102Y, 103Y Yellow (Y) signal processing unit 102K, 103K Black (K) Signal processing unit 104 Threshold variation determination unit

Claims (4)

Window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer);
Edge strength detection means for detecting edge strength within the window set by the window setting means;
Dither threshold fluctuation amount determining means for obtaining a dither threshold fluctuation amount according to the edge strength detected by the edge strength detection means;
Threshold holding means for holding in advance a threshold for converting the M-value image into an N-value image (N is an integer satisfying a relationship of M>N);
An N value that obtains a new threshold value based on the threshold value and the dither threshold value variation amount obtained by the dither threshold value variation determining means, and converts the M value image into N values based on the new threshold value and the M value image signal. And
An image processing apparatus comprising: Window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer);
Edge strength detection means for detecting edge strength within the window set by the window setting means;
A pixel value fluctuation amount determining means for obtaining a pixel value fluctuation amount according to the edge strength detected by the edge strength detection means;
Threshold holding means for holding in advance a threshold for converting the M-value image into an N-value image (N is an integer satisfying a relationship of M>N);
A new pixel value is obtained based on the M-value image signal and the pixel value fluctuation amount obtained by the pixel value fluctuation amount determining means, and the M-value image is converted into an N-value based on the new pixel value and the threshold value. N-value conversion means;
An image processing apparatus comprising: Window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer);
Detecting means for detecting edge strength and edge direction in the window set by the window setting means;
First fluctuation amount determining means for obtaining a dither threshold fluctuation amount according to the edge intensity detected by the detection means;
Second variation amount determining means for obtaining a dither threshold variation amount corresponding to the pixel in the edge direction detected by the detection means;
Threshold holding means for holding in advance a threshold for converting the M-value image into an N-value image (N is an integer satisfying a relationship of M>N);
A new threshold value is obtained based on the threshold value, the dither threshold fluctuation amount obtained by the first fluctuation amount determining means and the dither threshold fluctuation amount obtained by the second fluctuation amount determining means, and the new threshold value and the M value are obtained. N-value conversion means for converting the M-value image into an N-value based on an image signal;
An image processing apparatus comprising: Window setting means for setting an n × n (n is an integer) window for an M value image corresponding to an input M value image signal (M is an integer);
Detecting means for detecting edge strength and edge direction in the window set by the window setting means;
First fluctuation amount determining means for obtaining a pixel value fluctuation amount according to the edge intensity detected by the detection means;
Second fluctuation amount determining means for obtaining a pixel value fluctuation amount corresponding to the pixel in the edge direction detected by the detection means;
Threshold holding means for holding in advance a threshold for making the M-value image an N-value image (N is an integer satisfying a relationship of M>N);
A new pixel value is obtained based on the M-value image signal, the pixel value fluctuation amount obtained by the first fluctuation amount determination means and the pixel value fluctuation amount obtained by the second fluctuation amount determination means, and the new pixel N-value conversion means for converting the M-value image into an N-value based on a value and the threshold value;
An image processing apparatus comprising:

Images