JP2000013595A - Image processing method, device and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To decide whether or not image data to be a correction object are images by simple constitution and to prevent an image correction processing corresponding to a histogram from being performed with respect to these other than the images. SOLUTION: In this image processing method which prepares the histogram of a source image, setting an image processing condition based on the prepared histogram and image processing the source image, whether or not the source image is the image is decided based on the shape of the prepared histogram, and when it is decided that the source image is not an image, the image processing is not applied to the source image.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing method, apparatus and recording medium for performing image processing according to a histogram of an original image.

[0002]

2. Description of the Related Art With the spread of digital cameras and photo scanners in recent years, digitization of photo images has become easy, and in particular, the number of opportunities to handle photographic images as digital data on personal computers has increased. In addition, they can be edited on a personal computer using various application software, and can be easily arranged in a desired place by using the copy and paste function. However, the photographic input image often has image deterioration factors such as color cast for the following reasons.

For example, taking a digital camera as an example, C
An image captured by a CD camera may capture wavelengths such as infrared light that cannot be sensed by human eyes. Of course, processing such as an infrared cut filter is also performed, but the processing is not always perfect, and the color balance may be lost. Furthermore, it is known that humans adapt to differences in light source colors to see objects, but cameras record the differences directly on film, etc., so even if they reproduce color correctly colorimetrically Can also be felt out of color of human memory.

[0004] Especially in the field of photo printing, when a film taken by a silver halide camera is printed in a laboratory,
Generally, at the stage of printing on photographic paper, a function for analyzing a scene by image analysis of a photographed image and automatically correcting the scene is included. In order to obtain such a good output result, there have been proposed a number of methods for performing various image processing upon output and outputting.

[0005]

In order to obtain a good output result with an output device such as an ink jet printer, it is necessary to correct the digital data of the photo image as in the case of silver halide photography. It should be noted here that in photo printing and photo labs, the target is limited to photographs. However, when using an output device such as an ink jet printer or a color laser, or printing from a personal computer as one page of data, photographs (image images), text, and graphics such as figures and pictures are mixed. It is necessary to assume that.

That is, there has been a problem in that if the image correction performed to obtain a good output result with respect to an image image is applied to graphics or the like, a problem occurs.

SUMMARY OF THE INVENTION The present invention has been made to solve such a problem, and it is determined with a simple configuration whether image data to be corrected is an image image and a histogram other than the image image is determined according to a histogram. It is an object to prevent performing image correction processing.

[0008]

In order to achieve the above object, the present invention provides a method for generating a histogram of an original image, setting image processing conditions based on the generated histogram, and performing image processing on the original image. An image processing method for determining whether or not the original image is an image image based on the shape of the created histogram, and when it is determined that the original image is not an image, On the other hand, the image processing is not performed.

[0009]

(Embodiment 1) Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

FIG. 1 shows a schematic example of a system according to this embodiment. A printer 105 such as an ink jet printer and a monitor 106 are connected to the host computer 100. Host computer 100
Is an application software 101 such as a word processor, a spreadsheet, an Internet browser, etc., and an OS (OperatingS
ystem) 102, depending on the application OS 102
The printer driver 103 that processes various drawing commands (image drawing command, text drawing command, graphics drawing command) indicating an output image issued by the printer driver and creates print data, and processes various drawing commands issued by an application. And a monitor driver 104 for displaying on the monitor 106 as software.

The host computer 100 includes a central processing unit CPU 108 and a hard disk driver HD 10 as various hardware on which the software can operate.
7, a random access memory RAM 109, a read only memory ROM 110, and the like.

As an embodiment shown in FIG. 1, for example, Microsoft Windows 95 is used as an OS on a commonly-used IBM AT compatible personal computer, an arbitrary printable application is installed, and a monitor and a printer are connected. This embodiment is considered as one embodiment.

In the host computer 100, based on the display image displayed on the monitor, the application 10
In step 1, output image data is created using text data classified as text such as characters, graphics data classified as graphics such as figures, image image data classified as natural images, and the like. When printing out the output image data, the application 101 issues a print output request to the OS 102, and the graphics data portion is a graphics drawing command, and the image image data portion is a drawing command indicating an output image composed of an image drawing command. The group is issued to the OS 102. OS102
Receives an output request from the application and issues a rendering command group to the printer driver 103 corresponding to the output printer. The printer driver 103 processes a print request and a drawing command group input from the OS 102, creates print data printable by the printer 105, and transfers the print data to the printer 105. When the printer 105 is a raster printer, the printer driver 103 sequentially performs image correction processing on a drawing command from the OS, and rasterizes the drawing command sequentially into an RGB 24-bit page memory. The contents of the page memory are converted into a data format printable by the printer 105, for example, CMYK data, and transferred to the printer.

The processing performed by the printer driver 103 will be described with reference to FIG.

The printer driver 103 performs an image correction process described later on the color information included in the drawing command group input from the OS 102 by the image correction processing unit 120. First, the printer correction processing unit 121 rasterizes a drawing command using the color information subjected to the image correction processing, and generates a raster image on an RGB 24-bit page memory. Then, a masking process, a gamma correction process, a quantization process, and the like according to the color reproducibility of the printer are performed on each pixel to generate CMYK data depending on the printer characteristics, and transfer the CMYK data to the printer 105.

Next, an image correction process performed independently for each original image by the image correction processing unit 120 will be described with reference to FIG.

The image correction processing (color fogging correction and exposure correction) in this embodiment is processing for an image as described above, and a good output result can be obtained for an image image. However, if the image correction processing is applied to graphics or the like, the image quality may be degraded.

Therefore, in the present embodiment, it is determined whether or not the original image is an image, and the image correction processing is performed only on the image.

First, in step S5, it is determined whether or not the drawing command indicating the original image input from the application via the OS is an image drawing command. Here, if the drawing command is not an image drawing command such as a graphic drawing command, it is determined that the original image is not an image image, and the image correction process is not performed on the original image.

On the other hand, if the command is an image drawing command, it is determined that the original image may be an image image, and a luminance histogram is created in step S10. Details of the luminance histogram creation method will be described later.

In step S20, whether or not image correction processing should be performed on the original image is determined based on the number of luminances whose frequency is 0 in the histogram. That is, it is determined whether there is a possibility that the original image is an image image.

In a normal image, the frequency of each luminance is distributed as a whole as shown in FIG. On the other hand, a special image such as graphics is often composed of a specific color, and for example, often has a discrete distribution as shown in FIG. This can be understood by considering a graph composed of, for example, about 16 colors.

Therefore, when the number of 0 frequencies of the histogram is calculated and is equal to or larger than a predetermined value (for example, 100 when the threshold value is empirically obtained in the case of 256 gradations, etc.), the normal value is calculated. Judge that the image is not an image, and do not perform color correction.

Next, if it is determined in step S20 that the image should be corrected, a highlight point HL and a shadow point SD are determined based on the histogram in step S30.

In step S40, it is determined whether or not image correction should be performed based on the difference between the highlight point HL and the shadow point SD, that is, the distance. That is, it is determined whether or not the original image is an image. In step S40, if the difference is smaller than the predetermined value, the image correction processing is not performed because the image is not an image image.

This is because, for example, as shown in FIG. 6, when the histogram distribution is made up of a certain luminance, FIG.
As is clear from the comparison, the histogram of the image image is unnatural. Therefore, there is a high possibility that the image is a graphic such as a computer graphic or an intentionally created image, and the image correction processing should not be performed.

Then, an image correction process based on the image correction processing condition obtained based on the luminance histogram is performed only on the image finally determined to be subjected to the image correction (step S50). As image correction processing,
The color cast correction, exposure, and saturation correction, which will be described later, are performed.

As described above, according to the present embodiment, an unnatural original image is detected and excluded as an image image from the shape of the histogram such as the luminance of the original image, and the image correction processing is performed only on the image image. I do.

That is, it is possible to prevent the image correction processing from being performed on an image such as graphics having a special histogram shape that is clearly different from the histogram shape of the image image. Further, by observing the distance between the highlight value and the shadow value obtained from the histogram, an unnatural luminance distribution as a photo image, for example, an image created with a certain range of luminance created by CG can be obtained. Performing the correction process can be prevented.

(Creation of Luminance Hiss and Gram) FIG. 7 is a flowchart for creating a luminance histogram in this embodiment.

In FIG. 7, when a routine for creating a luminance histogram of an original image is entered in S81, a selection ratio of pixels used for creating a luminance histogram is determined from pixels of the original image in S82. In the present embodiment, in the case of data of 350,000 pixels, a luminance histogram is created for all the pixels (selection ratio 100%), and when an original image having more than 350,000 pixels is input, the total number of pixels is calculated. Pixel selection (sampling) is performed according to the ratio of numbers. That is, when an original image of 3.5 million pixels is input, one pixel per ten pixels (selection ratio 10
%), A luminance histogram is created. In the present embodiment, n is obtained by the following equation.

N = int (total number of pixels of original image / reference pixel number 350,000) (however, when n <1, n = 1, n is an integer) Then, in S83, the counter for managing the raster number is reset / The counter is set, and the counter is incremented in S84.

In the present embodiment, since the pixel thinning (sampling) is performed in units of raster, the above-described selection ratio is 10%.
In the case of, when the remainder obtained by dividing the raster number by 10 is 0, the processing is performed on the pixels belonging to the raster (S85).

[If (raster number Mod n) = 0 target raster else non-target raster] If the processing raster is the non-target raster, the process returns to S84. In the case of the target raster, the process proceeds to S86, where luminance conversion and chromaticity conversion are performed on each pixel belonging to the raster. The luminance conversion and the chromaticity conversion in the present embodiment are performed by the following equations. Note that the luminance and chromaticity conversions are not limited to the following equations, and various equations can be used as shown in the related art.

Y (luminance) = int (0.30R + 0.
59G + 0.11B), (Y is an integer) C1 (chromaticity) = RY C2 (chromaticity) = BY

In this embodiment, in order to improve the detection accuracy of the white position (highlight point) and the black position (shadow point), the saturation is calculated by the following equation, and the saturation is calculated from a predetermined saturation value (Sconst). It is determined whether it is larger (S87). The information of the high-saturation pixels is not reflected on the luminance histogram.

Saturation S = sqrt (C1 ＾ 2 + C2 ＾ 2) That is, in the case of (S> Sconst), the process returns to S86 and the data of the pixel is not reflected in the subsequent processing. The effect of this processing will be described with a specific example. For example, in many cases, it is less likely that a yellow pixel (R = G = 255, B = 0) is determined to have a yellow hue color than to determine that an achromatic pixel is colored yellow. . However, when the brightness of the pixel is obtained by the above calculation formula, the brightness value becomes “2
26 ", which means that the pixel has extremely high luminance. Therefore, if the pixel is included in the creation of the luminance histogram, an error may occur when the white position is detected.

According to the above equation, the saturation of the pixel is “22”.
7 "indicates that the color is sufficiently high in color. Therefore, in the present embodiment, a predetermined saturation (Sconst) is determined,
Pixels with the predetermined saturation or higher are not included in the luminance histogram.

Therefore, it is possible to prevent an error from occurring in the white position detection due to the pixel, and to improve the accuracy of the white position detection.

After the determination in S87, a luminance histogram is created for pixels satisfying the condition (S <Sconst) (S88). Here, since the pixel data RGB handled in this embodiment is 8-bit (256 gradation) data, the luminance Y is also converted to a depth of 256. Therefore, the luminance histogram calculates how many pixels having 256 luminance values from 0 to 255 exist.

Since the calculated values of C1 and C2 are used as data for calculating the average chromaticity of the pixels belonging to each luminance value at the time of color cast correction later, the data is held as follows in this embodiment. In the form of a structure array variable from 0 to 255, three members of frequency, C1 cumulative value, and C2 cumulative value are set, and the calculation result for each pixel is reflected in each member.

It is determined whether or not the processing has been completed for all the pixels of the target raster (S89). If unprocessed pixels remain in the raster, the flow returns to S86 to repeat the processing from S86. When the processing of all pixels in the raster is completed, S90
It is determined whether or not an unprocessed raster remains. If all rasters have been completed, the process ends in S91. If an unprocessed raster remains, the process returns to S84 and repeats the above processing.

As described above, by creating a luminance histogram while selecting pixels of the original image, a luminance histogram with the minimum necessary number of pixels and taking into account the improvement of the accuracy in detecting white and black positions later. Can be created.

(Determination of Highlight Point and Shadow Point) When the luminance histogram is completed, a white position (white point) and a black position (shadow point) are determined from the histogram. In the present embodiment, the cumulative luminance value is 17 from the ends of the luminance value 0 and the luminance value 255 toward the center.
The point which becomes 50 is defined as a white position and a black position.

When the frequency of a pixel having a luminance n is set as Yn, Y
0 + Y1... And the cumulative frequency is obtained.
The luminance value (Yk) when the value exceeds 750 is set as the luminance value (k) at the black position. Next, the average chromaticity of the pixel having the luminance of Yk is obtained. As described above, when the luminance histogram is created, the cumulative chromaticity of each luminance value is calculated (the cumulative chromaticity of the pixel of luminance n is assumed to be C1n total and C2n total). Average chromaticity C1k,
Find C2k.

C1k = C1k total / Yk C2k = C2k total / Yk

Similarly, the white position is determined. Y255 + Y
254+... And the cumulative frequency is obtained, and the cumulative frequency is 1
The luminance value (Yw) when the value exceeds 750 is set as the luminance value (w) at the black position. Next, the average chromaticity of the pixel having the luminance of Yw is obtained. Average chromaticity C1w, C of pixel with luminance value w at white position
Find 2w.

C1w = C1w total / Yw C2w = C2w total / Yw In the “Y, C1, C2” color space, the white position (Yw, C1w, C2w) and the black position (Y
k, C1k, C2k).

In this embodiment, the luminance value is 0 and the luminance value is 25.
Although the cumulative frequency is calculated from the 5 luminance positions, a predetermined offset may be provided, for example, from the luminance value 1 and the luminance value 254.

(Color Fogging Correction) As described above, when the white position and the black position of the original image in the “Y, C1, C2” color space are obtained, the color fogging is subsequently corrected.

If the original image has no color cast and is an ideal image, the achromatic color is R = G = B and the white position,
The calculated value of the chromaticity at the black position is “C1w = C2w = C1k = C
2k = 0 ". However, if there is a color cast, in the direction of the hue being covered, in proportion to the degree of the covering,
(Yw, C1w, C2w) and (Yk, C1k, C2k)
Are inclined in the straight line (color solid axis) connecting the two. The color cast correction can be achieved by performing conversion so that the color solid axis and the Y axis coincide. The method can be achieved by rotating and translating the color solid, or by transforming the coordinate system.

In the present embodiment, first, the color solid of the original image is rotated so that the lowest luminance point (lower end point) of the color solid axis is the center of rotation and the color solid axis is the axis of rotation so as to be parallel to the Y axis.
Next, the position of the lowest luminance point is (Y ', C1', C
2 ') Transform the coordinate system to be the origin of space.

FIG. 8B shows the result of performing color cast correction on the color solid of FIG. 8A.

By the above processing, a conversion processing in which the lowest luminance point is the origin and the color solid axis coincides with the Y axis is realized.

In a system in which a rotation axis and a rotation angle are determined in a three-dimensional space, a method of obtaining a rotation matrix for rotating a solid at a desired angle is a known technique, and a detailed description thereof will be omitted.

As described above, each pixel of the original image is converted into luminance and chromaticity data (Y, C1, C2), and rotated and translated in a three-dimensional color space (Y ', C1', C2). ') Makes it possible to perform color cast correction.

(Exposure and Saturation Correction) The hue shift of the original image can be corrected by performing the above-mentioned color fogging correction. However, as a means for further improving the image level, exposure correction and saturation correction are performed. Do.

In the present embodiment, over- and under-exposures are simply determined, and γ correction is performed on the luminance signal to perform exposure correction accordingly.

Exposure correction is performed by a one-dimensional LUT that converts input luminance values 0 to 255 into output luminance values 0 to 255. The LUT according to the present embodiment has a luminance value “Yk” at a black position (shadow point), a luminance value “Yw” at a white position (white point), and a luminance value “T ′” at an inflection point existing therebetween. It can be expressed as two straight lines connecting points (see FIG. 9).

In the present embodiment, the luminance value “Yk” at the black position
Is converted into a luminance value “10”, and the input luminance value “Yw” at the white position is converted into a luminance value “245”. Further, the luminance value “T ′” of the inflection point is defined and converted as follows. Assuming that a luminance value forming a minimum distance between the color solid axis before color cast correction and the Y axis (luminance axis) is T, the difference between the luminance value T and the minimum luminance value of the color solid of the original image is an inflection point. Is assumed to be “T ′”. The luminance value T 'at the inflection point is converted to the luminance value "T".

That is, as shown in FIG. 3, the black position “Yk” has a luminance value “10” (point a), the inflection point “T ′” has a luminance value “T” (point b), and the white position “Yw”. Is changed to a luminance value “245” (c
Point). The luminance values of the other original images are converted along the straight lines connecting “a” and “b” and “b” and “c”, respectively, as indicated by the thick lines in FIG.

Further, the saturation correction can be performed, for example, as follows. For the chromaticities C1 and C2 of each original pixel, C1 "= n * C1 'C2" = n * C2' (where n is a saturation coefficient) The saturation is adjusted by adjusting the saturation coefficient "n". Correction can be easily performed.

Thus, the various corrections according to the present embodiment are completed. At this point, each pixel of the original image has been converted from the (R, G, B) color signal data to the (Y ", C1", C2 ") color space data. ', B
') Inverse conversion to color signal data. The inverse conversion is performed by the following equation.

R '= Y "+ C"G' = Y "-(0.3 / 0.59) * C1"-(0.
11 / 0.59) * C2 "B '= Y" + C2 "

(Other Embodiments) In the above-described embodiment, the so-called contrast adjustment is first performed in the image correction processing, and then the so-called contrast adjustment for correcting underexposure or overexposure is performed. . Also, the method of determining the highlight / shadow point and the algorithm relating to the image correction are not limited to the above methods, and various other methods can be used.

In the above-described embodiment, a simple average is used to create a brightness histogram. However, a histogram is created based on a color component indicating brightness created with a slight weighting on a blue component compared to a luminance signal. do it.

Further, in the above-described embodiment, the value whose frequency is 0 in the histogram is counted. However, for example, approximately 0 frequency such as 1 may be counted.

Further, software for realizing the functions of the above-described embodiment is installed in a device connected to the various devices or a computer in the system so as to operate various devices so as to realize the functions of the above-described embodiment. The present invention also includes a program code supplied and executed by operating a computer (CPU or MPU) of the system or apparatus according to a stored program to operate the various devices.

In this case, the program code itself of the software realizes the functions of the above-described embodiment, and the program code itself and means for supplying the program code to the computer, for example, the program code The storage medium storing the information constitutes the present invention.

As a storage medium for storing such a program code, for example, a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, magnetic tape, nonvolatile memory card, ROM or the like can be used.

When the computer executes the supplied program code, not only the functions of the above-described embodiment are realized, but also the OS (operating system) running on the computer or another program. Needless to say, the program code is also included in the embodiment of the present invention when the functions of the above-described embodiment are realized in cooperation with application software or the like.

Further, the supplied program code is stored in a memory provided in a function expansion board of a computer or a function expansion unit connected to the computer, and then stored in the function expansion board or the function storage unit based on the instruction of the program code. It is needless to say that the present invention includes a case where a provided CPU or the like performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

[0073]

As described above, according to the present invention, it is determined with a simple configuration whether image data to be corrected is an image image, and image correction processing according to a histogram is performed on an image other than the image image. Can be prevented.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating an example of a system configuration.

FIG. 2 is a diagram illustrating processing performed by a printer driver.

FIG. 3 is a diagram illustrating a process performed by an image correction processing unit.

FIG. 4 is a diagram illustrating an example of a luminance histogram in an image image.

FIG. 5 is a diagram illustrating an example of a luminance histogram in an image composed of a specific color.

FIG. 6 is a diagram showing an example of a luminance histogram in an image composed of a certain range of luminance.

FIG. 7 is a diagram showing a flow of a brightness histogram creation process.

FIG. 8 is a diagram illustrating color cast correction.

FIG. 9 is a diagram illustrating an LUT for performing exposure correction.

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor Nobuo Ogura 3-30-2 Shimomaruko, Ota-ku, Tokyo Inside Canon Inc. (72) Inventor Kentaro Yano 3-30-2 Shimomaruko, Ota-ku, Tokyo (72) Inventor Tetsuya Suwa 3-30-2 Shimomaruko, Ota-ku, Tokyo F-term (reference) 5C077 MP06 PP15 PP27 PP28 PP34 PP37 PP52 PP53 PQ19

Claims (8)

[Claims] An image processing method for creating a histogram of an original image, setting image processing conditions based on the created histogram, and performing image processing on the original image, comprising: Determining whether or not the original image is an image based on a shape; and determining that the image processing is not performed on the original image when determining that the original image is not an image. Method. 2. The method according to claim 1, wherein a value of which frequency is substantially zero in the created histogram is counted, and whether or not the original image is an image is determined according to the count result. The image processing method described in the above. 3. The method according to claim 1, wherein a highlight point and a shadow point of an original image are detected based on the histogram, and the image processing condition is set based on the detected highlight point and shadow point. The image processing method described in the above. 4. The image according to claim 1, further comprising: inputting a drawing instruction indicating the original image, and determining whether the original image is an image by analyzing the drawing instruction. Processing method. 5. The image processing method according to claim 1, wherein the image processing is independently performed on each original image forming the input image. 6. A method for detecting a highlight point and a shadow point of an original image based on the generated histogram, and determining whether the original image is an image based on the detected highlight point and shadow point values. 2. The image processing method according to claim 1, wherein: 7. An image processing apparatus, comprising: creating means for creating a histogram of an original image; setting means for setting image processing conditions based on the created histogram; and an image processing apparatus for performing image processing on the original image, And determining means for determining whether or not the original image is an image image based on the shape of the created histogram. If it is determined that the original image is not an image, the image is determined with respect to the original image. An image processing apparatus characterized by performing no processing. 8. A recording medium for recording a program readable by a computer, wherein a histogram of an original image is created, image processing conditions based on the created histogram are set, and image processing is performed on the original image. An image processing method for determining whether or not the original image is an image image based on the shape of the created histogram.If it is determined that the original image is not an image, A recording medium for recording a program for preventing the image processing from being performed.