JP2015089029A - Image evaluation device, image formation device, and picture quality evaluation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image evaluation device capable of precisely obtaining a quantitative evaluation result about gradation having a high relation with an evaluation value of gradation in which a human being observes an image for a gradation image to evaluate it subjectively.SOLUTION: A gradation image in which gradation changes continuously is measured to obtain image information related to gradation. On the basis of the image information of the gradation image, an evaluation value of gradation is for the characteristic representing change in image information relative to the change in gradation of the gradation image is calculated. A noise evaluation value is obtained which represents intensity of noise in the gradation image, and on the basis of the noise evaluation value, the evaluation value of gradation is corrected.

Description

  The present invention relates to an image evaluation apparatus and an image evaluation method for evaluating a multi-gradation image, and an image forming apparatus such as a copying machine, a facsimile machine, and a printer provided with the image evaluation apparatus.

  Conventionally, in this type of image forming apparatus, gradation is one of important characteristics of an output image. The gradation of the image is quantified by the total number of gradation levels (levels), and the greater the total number of gradation levels, the smoother the gradation can be expressed. In the case of a color image, the number of gradation levels is set for each color, and the greater the number of gradation levels, the smoother the color density (lightness or saturation) can be expressed. Here, the total number of gradation steps is a gradation. For example, when the gradation step is 256 steps (8 [bits]), it is referred to as 256 gradations. Further, the value assigned to each level of gradation is a gradation value (for example, 0, 1,..., 255 in the case of 256 gradations). For example, an electrophotographic color image forming apparatus usually forms a color image by combining four single colors of cyan (C), magenta (M), yellow (Y), and black (K). For each color of CMYK, the color from the background color of the paper (transfer medium) to the color with the highest density (lightness or saturation) that can be expressed by each single color is expressed by a predetermined gradation (for example, 256 gradations). can do.

  As an image evaluation apparatus for evaluating the gradation of the image, an image evaluation apparatus disclosed in Patent Document 1 is known. In this image evaluation apparatus, a gradation image whose gradation value changes continuously is evaluated so as to cope with a phenomenon such as gradation unevenness in the gradation image used in subjective gradation evaluation. It is used as At least one piece of color information (image information) of brightness information, density information, intensity information, saturation information, chromaticity information, and hue information of the gradation image is measured to evaluate gradation in the gradation image.

  However, in the image quality evaluation apparatus described in Patent Document 1, there is no correlation between the evaluation result of the gradation obtained by measuring the gradation image and the evaluation result actually evaluated by human observation of the gradation image. It is enough.

  SUMMARY OF THE INVENTION The present invention has been made in view of the above-described problems, and an object of the present invention is to quantify gradation having a high correlation with an evaluation value of gradation that is subjectively evaluated by observing an image of a gradation image. It is to provide an image forming apparatus that can accurately obtain a typical evaluation result.

  In order to achieve the above object, the invention of claim 1 is an image information acquisition unit that measures a gradation image in which gradation changes continuously and acquires image information related to the gradation, and the image information acquisition unit. An image evaluation unit comprising: a calculation unit that calculates an evaluation value of gradation in a characteristic indicating a change in the image information with respect to a change in the gradation of the gradation image based on the image information of the gradation image acquired in step The apparatus comprises: a noise evaluation value acquisition unit that acquires a noise evaluation value indicating a magnitude of noise in the gradation image; and a correction unit that corrects the evaluation value based on the noise evaluation value. Is.

  According to the present invention, it is possible to accurately acquire a quantitative evaluation result of gradation having a high correlation with an evaluation value of gradation that is subjectively evaluated by observing an image of a gradation image.

1 is a schematic configuration diagram illustrating an example of an image forming engine unit of an image forming apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating a configuration example of a control system of the image forming apparatus. Explanatory drawing which shows an example of the gradation image from which a gradation value changes continuously. The graph which measured the brightness change of the gradation image of FIG. The graph which digitized the absolute value of the lightness difference of the lightness of each gradation and +6 gradation. 6 is a graph obtained by calculating the difference between the maximum value and the minimum value of ± 5 gradations of each gradation from the graph of FIG. 7 is a graph showing the correlation between the gradation unevenness evaluation value calculated in FIG. 6 and the evaluation value obtained by the human eye through subjective evaluation. FIG. 7 is a graph showing a correlation between a gradation unevenness evaluation value obtained by correcting a gradation unevenness evaluation value calculated in FIG. 6 with a noise evaluation value and an evaluation value obtained by a human through subjective evaluation. FIG. 5 is an explanatory diagram in which a gradation image of several stages for measuring noise characteristics is arranged together with a gradation image. Explanatory drawing for calculating | requiring the granularity of several places in a gradation image.

Hereinafter, an embodiment in which the present invention is applied to an electrophotographic color image forming apparatus (hereinafter simply referred to as “image forming apparatus”) will be described.
FIG. 1 is a schematic configuration diagram illustrating an example of an image forming engine unit of an image forming apparatus according to an embodiment of the present invention. The image forming engine unit includes four image forming units serving as toner image forming units for forming yellow (Y), cyan (C), magenta (M), and black (K) toner images. The image forming apparatus also includes a transfer unit having the intermediate transfer belt 6 and the like, an optical writing unit (not shown), a fixing device 13, a paper feed cassette (not shown), and a scanner (not shown). ing.

  The four image forming units use Y, M, C, and K toners of different colors, but the other configurations are the same. The four image forming units are configured to be replaced at the same time by holding these units on a common holding body and detaching them integrally with the image forming apparatus main body. May be.

  Here, a C image forming unit for forming a C toner image will be described as an example. As shown in FIG. 1, the C image forming unit includes a drum-shaped photosensitive member 1C as a latent image carrier, a drum cleaning device 16C as a latent image carrier cleaning means, and a static eliminating device as a latent image carrier neutralizing means. (Not shown). Further, the C image forming unit includes a charging roller 2C as a charging unit, a developing device 4C as a developing unit, and the like.

  The photoreceptor 1C is rotationally driven in the clockwise direction of the arrow in the figure by a driving unit (not shown). The surface of the photoreceptor 1C is uniformly charged by generating a discharge between the charging roller 2C and the photoreceptor 1C while bringing the charging roller 2C to which the charging bias is applied into contact with or close to the photoreceptor 1C. The As a method for uniformly charging the photoconductor, a method using a charging charger may be adopted instead of a method in which a charging member such as a charging roller is brought into contact with or close to the photoconductor 1C.

  The surface of the photosensitive member 1C uniformly charged by the charging roller 2C is irradiated with a writing laser beam 3C emitted from an optical writing unit (not shown) as a latent image writing unit (exposure unit), so An electrostatic latent image is formed. The optical writing unit is controlled based on image information (image data) of an image to be formed (input image). The writing laser beam 3C from the optical writing unit is optically scanned in the main scanning direction on the surface of the photoreceptor 1C, for example, by separating the image area / non-image area based on the image information of the input image. The electrostatic latent image for C carried on the photoreceptor 1C is developed by a developing device 4C using C toner to become a C toner image, and is primarily transferred onto an intermediate transfer belt 6 described later.

  The drum cleaning device 16C removes transfer residual toner adhering to the surface of the photoreceptor 1C after the primary transfer process (primary transfer nip described later). The static eliminator (not shown) neutralizes the residual charge on the photoreceptor 1C after being cleaned by the drum cleaning device 16C. By this charge removal, the surface of the photoreceptor 1C is initialized and prepared for the next image formation.

  In the other Y, M, and K image forming units, Y, M, and K toner images are formed on the photoreceptors 1Y, 1M, and 1K in the same manner as the C image forming unit.

  Above the four image forming units, an optical writing unit (not shown) serving as a latent image writing unit (exposure unit) is disposed. The optical writing unit includes, for example, a laser diode as a light source and a laser driving unit that drives the laser diode by a pulse width modulation (PWM) method. The laser drive unit sets an exposure control PWM value as a density control set value sent from a print control unit 132, which will be described later, and a period during which laser light can be irradiated to an area for one pixel on the photosensitive member in one cycle. The laser diode is driven based on the predetermined pixel clock. The exposure control PWM value is a value for designating a time (pulse ON time) for irradiating a region corresponding to one pixel in one pixel clock period for each pixel, as described later. This value is set according to the density level value. The exposure control PWM value of each pixel is generated by a multi-value dither method, which will be described later, based on image information sent from an external device such as a scanner or a personal computer. Laser light emitted from the laser diode of the optical writing unit is optically scanned in the main scanning direction (direction along the rotation axis) of the surface of the photoconductors 1Y, 1C, 1M, and 1K that are rotationally driven. Electrostatic latent images for Y, C, M, and K are formed on the photoreceptors 1Y, 1C, 1M, and 1K.

  Also, below the four image forming units, a transfer unit is disposed as a transfer device for endlessly moving the endless intermediate transfer belt 6 as an intermediate transfer member in the counterclockwise direction in the drawing while stretching. Yes. In addition to the intermediate transfer belt 6, the transfer unit includes a driving roller 7, a secondary transfer counter roller 11, and a cleaning backup roller 17. Further, the transfer unit includes four primary transfer rollers 5Y, 5C, 5M, 5K, a secondary transfer roller 10, a belt cleaning device 18, a belt tension roller 9, and the like.

  The intermediate transfer belt 6 is stretched by a driving roller 7, a secondary transfer counter roller 11, a cleaning backup roller 17, and four primary transfer rollers 5Y, 5C, 5M, 5K, and the like disposed inside the loop. Yes. Then, it is moved endlessly in the same direction by the rotational force of the driving roller 7 that is driven to rotate in the counterclockwise direction in the figure by a driving means (not shown).

  The four primary transfer rollers 5Y, 5C, 5M, and 5K respectively sandwich the intermediate transfer belt 6 that is moved endlessly between the photoreceptors 1Y, 1C, 1M, and 1K. As a result, primary transfer nips for Y, C, M, and K in which the front surface of the intermediate transfer belt 6 and the photoreceptors 1Y, 1C, 1M, and 1K abut are formed. A primary transfer bias is applied to the primary transfer rollers 5Y, 5C, 5M, and 5K by a primary transfer bias power source (not shown). As a result, a primary transfer electric field is formed between the Y, C, M, and K toner images on the photoreceptors 1Y, 1C, 1M, and 1K, and the primary transfer rollers 5Y, 5C, 5M, and 5K. The Y toner formed on the surface of the Y photoconductor 1Y enters the Y primary transfer nip as the photoconductor 1Y rotates. Then, the image is primarily transferred from the photoreceptor 1Y to the intermediate transfer belt 6 by the action of the transfer electric field and nip pressure. The intermediate transfer belt 6 onto which the Y toner image has been primarily transferred in this way then passes sequentially through the primary transfer nips for C, M, and K. Then, the C, M, and K toner images on the photoreceptors 1C, 1M, and 1K are sequentially superimposed and superimposed on the Y toner image. A four-color superimposed toner image is formed on the intermediate transfer belt 6 by this superimposing primary transfer.

  The secondary transfer roller 10 of the transfer unit is disposed on the outer side of the loop of the intermediate transfer belt 6 so as to be pressurized toward the intermediate transfer belt 6, and between the secondary transfer counter roller 11 on the inner side of the loop. 6 is sandwiched. As a result, the secondary transfer roller 10 rotates while being in contact with the intermediate transfer belt 6 or a transfer sheet as a recording medium, and the secondary transfer roller 11 is brought into contact with the front surface of the intermediate transfer belt 6 and the secondary transfer counter roller 11. A nip is formed. While the secondary transfer roller 10 is grounded, a secondary transfer bias is applied to the secondary transfer counter roller 11 by a secondary transfer bias power source (not shown). As a result, a secondary transfer electric field for electrostatically moving negative polarity toner from the secondary transfer counter roller 11 side to the secondary transfer roller 10 side between the secondary transfer counter roller 11 and the secondary transfer roller 10. Is formed.

  Below the transfer unit, a paper feed cassette (not shown) that stores a plurality of transfer sheets in a bundle of sheets is disposed. In this paper feed cassette, a paper feed roller (not shown) is brought into contact with the uppermost transfer paper of the paper bundle, and the paper feed roller is rotated at a predetermined timing to transfer the transfer paper to the transfer paper transport path. Send to 15 A registration roller pair 12 is disposed near the end of the transfer paper conveyance path 15. The registration roller pair 12 stops the rotation of both rollers as soon as the transfer paper fed from the paper feed cassette is sandwiched between the rollers. Then, rotation driving is restarted at a timing at which the sandwiched transfer paper can be synchronized with the four-color superimposed toner image on the intermediate transfer belt 6 in the secondary transfer nip, and the transfer paper P is sent out toward the secondary transfer nip. . The four-color superimposed toner image on the intermediate transfer belt 6 that is in close contact with the transfer paper at the secondary transfer nip is batch-transferred onto the transfer paper by the action of the secondary transfer electric field and nip pressure, and combined with the white color of the transfer paper. A full-color toner image is obtained. The transfer paper having the full-color toner image formed on the surface in this manner is separated from the secondary transfer roller 10 and the intermediate transfer belt 6 by the curvature when passing through the secondary transfer nip.

  A secondary transfer bias output from a secondary transfer bias power source (not shown) is applied to the secondary transfer counter roller 11. As a result, the toner on the intermediate transfer belt 6 is electrostatically moved from the secondary transfer counter roller 11 side to the secondary transfer roller 10 side between the secondary transfer counter roller 11 and the secondary transfer roller 10 to transfer the toner. Secondary transfer is performed on paper.

  Untransferred toner that has not been transferred to the transfer paper adheres to the intermediate transfer belt 6 after passing through the secondary transfer nip. The transfer residual toner is cleaned by removing the surface of the intermediate transfer belt 6 by a belt cleaning device 18 that is in contact with the front surface of the intermediate transfer belt 6.

  A fixing device 13 is disposed on the right side of the secondary transfer nip in the drawing. The fixing device 13 forms a fixing nip with a fixing roller including a heat source such as a halogen lamp and a pressure roller that rotates while contacting the fixing roller with a predetermined pressure. The transfer sheet fed into the fixing device 13 is sandwiched between the fixing nips in such a posture that the unfixed toner image carrying surface is in close contact with the fixing roller. Then, the toner in the toner image is softened by the influence of heating and pressurization, and the full-color image is fixed on the transfer paper. The transfer paper discharged from the fixing device 13 passes through a post-fixing conveyance path and is then discharged outside the apparatus.

  In the image forming apparatus of the present embodiment, when a monochrome image is formed, a support plate (not shown) that supports the primary transfer rollers 5Y, 5C, 5M for Y, C, M in the transfer unit is moved. The primary transfer rollers 5Y, 5C, 5M are moved away from the photoreceptors 1Y, 1C, 1M. As a result, the front surface of the intermediate transfer belt 6 is separated from the photoreceptors 1Y, 1C, 1M, and the intermediate transfer belt 6 is brought into contact with only the K photoreceptor 1K. In this state, of the four image forming units, only the K image forming unit is driven to form a K toner image on the photoreceptor 1K.

  FIG. 2 is a block diagram illustrating a configuration example of a control system of the image forming apparatus according to the present embodiment. As shown in FIG. 2, the image forming apparatus of this embodiment includes an input / output unit 110, a printer controller 120, a printer unit 130 as an image forming unit, a scanner controller 140 as an image information acquisition unit, a scanner unit 150, and a host I. / F160. These are connected via a bus 170 so that they can communicate with each other.

  The printer controller 120 includes an I / F 121, a memory unit 122 as an image data storage unit, a print data generation unit 123, a gradation correction calculation unit 124 as a gradation unevenness correction unit, and the like. It is connected to the. The I / F 121 is an interface that connects the printer controller 120 to the printer unit 130, the input / output unit 110, the scanner controller 140, the scanner unit 150, and the host I / F 160. The I / F 121 transmits / receives various signals and data to / from these units via the bus 170. Specifically, the I / F 121 performs print control of the printer unit 130, transfer of print data to the printer unit 130, read control of the scanner unit 150 and reception of read data via the scanner controller 140. In addition, the display contents of the input / output unit 110 are controlled, the input data is acquired, the image data is received from the external device via the host I / F 160, the status of the image forming apparatus 100 itself is notified to the external device, and the like. . For example, a network such as a wired or wireless LAN, a communication line such as a serial communication line, or a USB signal line is connected to the host I / F 160, and the host I / F 160 is connected to an external device or the like via the communication line.

  The memory unit 122 includes, for example, a RAM, a ROM, and the like, and stores various parameters necessary for executing gradation correction processing such as a basic program, control code, font data, dither data, and γ table of the image forming apparatus 100. Is done. Further, the memory unit 122 stores evaluation image data (such as gradation image data in which all gradation values are arranged) for checking the state of the output image, pixel density level setting data, and the like. Here, the pixel density level setting data indicates a correspondence relationship between a plurality of pixel density level values that can be set for each pixel of the output image and a density control setting value (exposure control PWM value) used for controlling the density of the pixel. It is data.

  The print data generation unit 123 performs processing such as control code conversion of data to be transferred to the printer unit 130 based on print data received from an external device via the host I / F 160, operation screen display and setting of the input / output unit 110, and the like. I do. The print data generation unit 123 refers to various image parameters, font data, and the like in the memory unit 122 and the like as necessary.

  The gradation correction calculation unit 124 performs various processes used for the gradation correction process in the present embodiment. Details of the correction processing will be described later.

  The scanner controller 140 includes an I / F 141, a memory unit 142, a read data generation unit 143, a color conversion unit 144 as a first evaluation unevenness calculation unit, and the like, and is connected to the bus 170 through the I / F 141. The color conversion unit 144 also has functions as noise acquisition means and second evaluation unevenness acquisition means. The I / F 141 is an interface that connects the scanner controller 140 to the scanner unit 150, the input / output unit 110, the printer unit 130, and the host I / F 160. Send and receive data. Specifically, the I / F 141 performs scan control of the scanner unit 150, reception of read data from the scanner unit 150, and the like. The I / F 141 controls display contents of the input / output unit 110, acquires input data, transmits image data to an external apparatus via the host I / F 160, notifies the external apparatus of the state of the image forming apparatus 100, and the like. I do.

  The read data generation unit 143 generates a digital image in a format such as TIFF or JPEG based on the colorimetric values of the three primary colors R (red), G (green), and B (blue) read by the scanner unit 150. To do. The read data generation unit 143 transmits the generated digital image to the external device via the host I / F 160. Further, when the read data is data obtained by reading a gradation image for checking gradation unevenness, the read data generation unit 143 transfers this data to the printer controller 120.

  The color conversion unit 144 converts the RGB light three primary color data values read by the scanner unit 150 into C (cyan), M (magenta), Y (yellow) color three primary colors, K (black) color data, and the like. Perform the conversion process. Then, this color conversion process is executed in generation of read data of an image read by the scanner unit 150 and conversion of read values of a gradation image.

  The printer unit 130 includes an I / F 131, a print control unit 132, and the like. Then, under the control of the print control unit 132, based on the image data (print data) of the output target image received from the printer controller 120 via the I / F 131 and the print control command, the image of the three primary colors is printed on the transfer paper. Process.

  The scanner unit (image reading unit) 150 includes an I / F 151, a reading control unit 152, and the like. The scanner unit 150 performs main scanning and sub-scanning on a document set on a document reading glass based on a scanner command input from the scanner controller 140 via the I / F 151. Then, the scanner unit 150 performs photoelectric conversion using a photoelectric conversion element such as a CCD, and acquires an image of a document as a read value of RGB three primary colors.

  The input / output unit 110 includes an I / F 111, an input unit 112, an output unit 113, and the like. The I / F 111 exchanges signals and data with the printer controller 120 and the scanner controller 140 via the bus 170.

  The input unit 112 is, for example, a numeric keypad, a dedicated operation key, a touch panel, and the like. The input unit 112 acquires user input operation contents and outputs them to the printer controller 120 and the scanner controller 140 via the I / F 111. The input unit 112 may be used when the operator performs the gradation step correction mode.

  An LCD, LED, or the like is used as the output unit 113, and a touch panel that functions as the input unit 112 is superimposed on the LCD. The output unit 113 displays information from the printer controller 120, the scanner controller 140, and the like.

  The host I / F 160 transmits and receives an image formation request (print request), image data (print data), machine information, and the like from an external device.

  Next, an evaluation method for evaluating gradation unevenness for a cyan (C) image output using the image forming apparatus 100 will be described.

  FIG. 3 is an example of a gradation image output by the image forming apparatus 100, and is a gradation image whose gradation value continuously changes from 0 to 255. In a gradation image, it is ideal that the brightness changes smoothly. However, in the gradation image shown in FIG. 3, stripe-like unevenness (gradation unevenness) that appears darker than the adjacent areas is visually recognized around 130 gradations. The

  FIG. 4 is a graph in which the gradation image shown in FIG. 3 is read by the scanner unit 150 of the image forming apparatus 100 and the change in brightness is measured. In the gradation image shown in FIG. 3, gradation values change in the horizontal direction, but all the vertical directions have the same gradation value. Further, since the gradation value in the horizontal direction is a total of 256 gradations from 0 to 255, for example, if the horizontal width of the image is 256 [mm], the range in the horizontal direction 1 [mm] has the same gradation value. . The graph of FIG. 4 is created using values obtained by measuring the brightness of a plurality of locations within the same gradation value range and averaging them.

  Also in the graph shown in FIG. 4, a change in data (concave shape) different from the other portions is seen around the gradation value of 130 (A portion). These locations (gradations) substantially coincide with the gradation in which “dark streaky unevenness” (gradation unevenness) occurs in the gradation image shown in FIG. In the graph shown in FIG. 4, the lightness L * decreases as the gradation value increases. However, the “dark streaky unevenness” ( (Gradation unevenness) occurs.

  5 and 6 are graphs for obtaining evaluation values by digitizing gradation unevenness. FIG. 5 is a graph showing the absolute value of the difference between the lightness of each gradation and the lightness of +6 gradations. is there. FIG. 6 is a graph showing the difference between the maximum value and the minimum value of about 10 gradations (± 5 gradations) before and after each gradation in the data of the graph of FIG.

  As shown in the graph of FIG. 5, the brightness difference ΔL * changes greatly in the vicinity of 130 gradations, and it can be seen that gradation unevenness is more conspicuous. Note that the gradation unevenness value on the vertical axis of the graph shown in FIG. 6 is the first gradation unevenness evaluation value. For example, the first gradation unevenness evaluation value near the 130th gradation of the gradation image is It is about 1.7.

  FIG. 7 shows the first gradation unevenness evaluation value described with reference to FIG. 6 and the human eyes by visual observation about the gradation unevenness occurring in the gradation image output in several different modes with three different types of printers. It is a graph which shows the correlation with the evaluation value calculated | required by subjective evaluation. Subjective evaluation by humans is also called sensory evaluation, and can be evaluated by a method generally performed as a sensory evaluation test. Specifically, first, a procedure for determining five levels of scale images by a paired comparison test and determining which level of the scale corresponds to the other images is performed on a dozen subjects, The evaluation value of the image is calculated. As shown in FIG. 7, the correlation contribution ratio between the first gradation unevenness evaluation value obtained by the physical method described with reference to FIG. 6 and the subjective evaluation value by the sensory evaluation test is 0.70. ing.

Here, the correlation contribution rate is the accuracy of the regression analysis, that is, the degree of fit of the regression equation that approximates the actual measurement value used for the regression analysis, and is represented by the square of the correlation coefficient r. The correlation coefficient r is a scale representing the degree of linear relationship between two corresponding variables such as (x1, y1), (x1, y1), ..., (x1, y1). It is. If the absolute value of the correlation coefficient is close to 1, it indicates that the relationship between x and y is strong, and if it is close to 0, it indicates that the relationship between x and y is small. The correlation coefficient r and the correlation contribution rate r ² have a relationship of r ≦ r ² , and are generally said to be strongly correlated when r ≧ ± 0.7 and r ² ≧ 0.5.

  Even if the first gradation unevenness evaluation value is the same in the same hue and the same lightness range, the sensory evaluation values determined by the human eye may be different. As a result of intensive studies by the present inventors on this reason, it has been found that the appearance of gradation unevenness changes depending on the difference in noise characteristics (particularly granularity) of gradation images. From this, it is concluded that by correcting the first gradation unevenness evaluation value calculated from the change in color information with the granularity, it is possible to evaluate gradation unevenness highly correlated with human sensory evaluation values. Obtained.

  FIG. 8 shows an evaluation value (hereinafter referred to as “noise evaluation value”) of noise characteristics in a halftone image such as gradation with respect to the first gradation unevenness evaluation value obtained by the physical method described with reference to FIG. .) Is a graph showing the correlation between the second gradation unevenness evaluation value subjected to the correction according to FIG. As shown in FIG. 8, the correlation contribution rate is improved to 0.87 by performing the correction using the noise evaluation value. This correction is made because gradation unevenness changes in appearance due to the feeling of roughness around the surroundings and the graininess, and when the graininess is poor, the gradation unevenness is less noticeable. An equation is created and corrected so that the gradation unevenness evaluation value becomes worse when the graininess is good and the gradation unevenness evaluation value becomes better when the graininess is bad.

  For the correction, the color granularity (CG) equation (1) obtained by quantifying the granularity was used. Formula (2) is a basic formula of Formula (1) representing granularity (GS), and is an evaluation formula of Dooley et al. Using a winner spectrum and visual spatial frequency characteristics (Visual Transfer Function: VTF) ( Non-patent document 1).

The color granularity (CG) formula (1) is obtained by applying the graininess (GS) formula (2) to the chromaticity component and taking a linear sum with the brightness component.
Here, WS _B (u), WS _C1 (u), WS _C2 (u) in the formula (1) are Wiener spectra of the lightness component and the chromaticity component, and VTF _B (u), VTF _C1 (u ), VTF _C2 (u) is the visual spatial frequency characteristic (VTF) for the lightness component and the chromaticity component. H (B) is a function having the average brightness B as a variable, and a function for correcting the formula (1) so that the formula (1) is satisfied even when the average brightness is different as in the correction function for the average density in the formula (2). It is. P _B , P _C1 , and P _C2 are weights representing the contribution of each component (lightness and two chromaticities) to the graininess, and C is a constant.
In Equation (2), u is a spatial frequency, WS (u) is a Wiener spectrum, and VTF (u) is a visual spatial frequency characteristic. The term exp (1.8D) is a function with the average density D as a variable for correcting the difference between density and brightness perceived by humans.

  FIG. 9 shows a measurement image in which gradation images and several halftone patch images are arranged for measuring noise characteristics. The noise evaluation value is calculated by measuring the granularity in the patch image portion shown in FIG. 9, and the first gradation unevenness evaluation value calculated from the gradation image is corrected using this noise evaluation value, and the second floor is calculated. A tone unevenness evaluation value can be obtained.

  The granularity is not limited to a patch image, and may be obtained from a gradation image. FIG. 10 is an explanatory diagram for measuring graininess from a gradation image. As shown in FIG. 10, the granularity is obtained at several points surrounded by a broken line in the gradation image, and the granularity is measured in the lightness region close to the lightness of each gradation unevenness occurrence part to calculate the noise evaluation value. Then, the first gradation unevenness evaluation value calculated from the gradation image may be corrected using this noise evaluation value to obtain the second gradation unevenness evaluation value.

  The second gradation unevenness evaluation value calculated as described above may be used to generate image data so that the gradation correction calculation unit 124 corrects gradation unevenness. For example, the gradation correction calculation unit 124 determines an exposure control PWM value corresponding to the pixel density level value of the gradation to be corrected based on the second gradation unevenness evaluation value. Then, the gradation correction calculation unit 124 stores the pixel density level setting data updated with the determined exposure control PWM value in the memory unit 122 (new storage or overwrite storage for update). In the image forming apparatus according to the present embodiment, the evaluation accuracy of gradation unevenness is improved, and correction is performed so that gradation unevenness is not recognized by human vision. Further, it is possible to prevent useless operations such as correcting gradation unevenness when correction is not necessary.

What has been described above is merely an example, and the present invention has a specific effect for each of the following modes.
(Aspect A)
Image information acquisition means such as a read data generation unit 143 that measures a gradation image whose gradation changes continuously and acquires image information related to the gradation, and image information of the gradation image acquired by the image information acquisition means And a calculation means such as a color conversion unit 144 for calculating an evaluation value of gradation in a characteristic indicating a change in image information with respect to a change in gradation of the gradation image based on the image evaluation of the scanner controller 140 or the like In the apparatus, a noise evaluation value acquisition unit such as a color conversion unit 144 that acquires a noise evaluation value indicating the magnitude of noise in the gradation image, and a color that corrects the evaluation value of the gradation property based on the noise evaluation value Correction means such as a conversion unit 144.
According to this, as described in the above embodiment, the evaluation value of the gradation property in the characteristic indicating the change in the image information with respect to the change in the gradation of the gradation image is calculated. The evaluation value is corrected based on a noise evaluation value indicating the magnitude of noise of the gradation image that affects the human subjective evaluation of the gradation in the gradation image. By the correction based on the noise evaluation value, it is possible to obtain a gradation evaluation value having a high correlation with human subjective evaluation. Therefore, it is possible to accurately acquire a quantitative evaluation result of gradation that has a high correlation with an evaluation value of gradation that is subjectively evaluated by observing an image of a gradation image.
(Aspect B)
In the aspect A, a uniform halftone image is formed for a predetermined gradation value selected from among a plurality of gradation values in the gradation image, and a noise evaluation value indicating the magnitude of noise in the halftone image is obtained. calculate.
According to this, as described in the above embodiment, a noise evaluation value can be obtained with high accuracy for a predetermined gradation value in a gradation image.
(Aspect C)
In the aspect B, the halftone image is formed with respect to a plurality of different gradation values in the gradation image, and a noise evaluation value indicating the magnitude of noise in the halftone image is calculated for each of the plurality of halftone images. .
According to this, as described in the above embodiment, the first gradation unevenness is obtained by using the noise evaluation values calculated for each of a plurality of halftone images formed for a plurality of different gradation values in the gradation image. The evaluation value can be corrected. Accordingly, it is possible to obtain a gradation evaluation result having high correlation with a gradation evaluation value subjectively evaluated by observing an image of a gradation image with higher accuracy.
(Aspect D)
In the aspect A, the noise evaluation value is calculated based on image information acquired for an image portion corresponding to a gradation value within a predetermined gradation range in the gradation image.
According to this, as described in the above embodiment, the first gradation unevenness evaluation value and the noise evaluation value can be calculated from one gradation image, and are calculated by forming separate images. Compared to the case, it is possible to reduce the cost by reducing the color material used for image formation.
(Aspect E)
In any one of the above aspects A to D, an absolute value of the difference between the image information acquired for each of a plurality of image portions having different gradation values by a predetermined number in the gradation image is calculated, and for each predetermined gradation range. Then, the difference between the maximum value and the minimum value of the absolute value calculated respectively is calculated, and the evaluation value of gradation is calculated based on the magnitude of the difference between the maximum value and the minimum value.
According to this, as described in the above embodiment, it is possible to accurately and easily identify the gradation value in which gradation unevenness occurs in the gradation image and calculate the evaluation value of gradation.
(Aspect F)
In any one of the above aspects A to E, brightness is used as image information used to calculate the evaluation value of gradation.
According to this, as described in the above embodiment, the gradation can be evaluated regardless of the hue of the image.
(Aspect G)
In any of the above aspects A to F, an evaluation value indicating the degree of graininess in the gradation image is used as the noise evaluation value.
According to this, as described in the above embodiment, in terms of human vision, the appearance of gradation unevenness changes due to the difference in granularity as the noise characteristics of the gradation image. By correcting the evaluation value indicating the degree of graininess as a noise evaluation value, the gradation characteristic is highly quantitatively correlated with the evaluation value of the gradation characteristic obtained by human observation and subjective evaluation. More accurate evaluation results can be obtained.
(Aspect H)
In an image forming apparatus including a storage unit such as a memory unit 122 that stores image data of a multi-tone image and an image forming unit such as a printer unit 130 that forms an image based on the image data, the above aspects A to A Any image evaluation apparatus of F is provided.
According to this, as described in the above embodiment, the quantitative evaluation result of the gradation having a high correlation with the evaluation value of the gradation that is subjectively evaluated by observing the image with respect to the gradation image is obtained. It can be acquired with high accuracy.
(Aspect I)
In the aspect H, image data processing such as a gradation correction calculation unit 124 that corrects image data of a multi-gradation image to be formed based on a gradation evaluation value corrected based on a noise evaluation value is further provided. It was.
According to this, as described in the above embodiment, it is possible to form a high-quality multi-gradation image free from phenomena such as gradation unevenness, gradation skipping, and collapse. Further, when there is no gradation unevenness, correction of image data of a multi-gradation image to be formed can be avoided, so that unnecessary correction operation of image data can be prevented.
(Aspect J)
An image quality evaluation method for evaluating the image quality of a multi-tone image, the step of measuring a gradation image whose gradation changes continuously and acquiring image information related to the gradation; and the image information of the gradation image A step of calculating an evaluation value of gradation in a characteristic indicating a change in image information with respect to a change in gradation of the gradation image, and a step of obtaining a noise evaluation value indicating a magnitude of noise in the gradation image; And correcting the tone evaluation value based on the noise evaluation value.
According to this, as described in the above embodiment, the evaluation value of the gradation property in the characteristic indicating the change in the image information with respect to the change in the gradation of the gradation image is calculated. The gradation evaluation value is corrected based on a noise evaluation value indicating the magnitude of noise in the gradation image that affects the human subjective evaluation of gradation in the gradation image. By the correction based on the noise evaluation value, it is possible to obtain a gradation evaluation value having a high correlation with human subjective evaluation. Therefore, it is possible to accurately acquire a gradation evaluation value having high correlation with a gradation evaluation value subjectively evaluated by human observation of a gradation image.

1 (1Y, 1C, 1M, 1K) Photoconductor 2C Charging roller 3C Writing laser beam 4C Developing device 5 (5Y, 5C, 5M, 5K) Primary transfer roller 6 Intermediate transfer belt 7 Driving roller 9 Belt tension roller 10 Secondary Transfer roller 11 Secondary transfer counter roller 12 Registration roller pair 13 Fixing device 15 Transfer paper transport path 16C Drum cleaning device 18 Belt cleaning device 120 Printer controller 122 Memory unit 124 Tone correction calculation unit 130 Printer unit 140 Scanner controller 144 Color conversion unit

JP 2003-16443 A

Ricoh Technical Report, September 1997, No. 23, pages 53-59

Claims (10)

Image information acquisition means for measuring gradation images whose gradation changes continuously and acquiring image information related to the gradation;
Calculation means for calculating an evaluation value of gradation in a characteristic indicating a change in the image information with respect to a change in gradation of the gradation image, based on the image information of the gradation image acquired by the image information acquisition means; In an image evaluation apparatus comprising:
Noise evaluation value acquisition means for acquiring a noise evaluation value indicating the magnitude of noise in the gradation image;
An image evaluation apparatus comprising: correction means for correcting the evaluation value of gradation based on the noise evaluation value. The image evaluation apparatus according to claim 1,
A uniform halftone image is formed with respect to a predetermined gradation value selected from a plurality of gradation values in the gradation image, and a noise evaluation value indicating the magnitude of noise in the halftone image is calculated. An image evaluation apparatus. The image evaluation apparatus according to claim 2,
The halftone image is formed for a plurality of different gradation values in the gradation image, and a noise evaluation value indicating the magnitude of noise in the halftone image is calculated for each of the plurality of halftone images. Image evaluation device. The image evaluation apparatus according to claim 1,
An image evaluation apparatus, wherein the noise evaluation value is calculated based on image information acquired for an image portion corresponding to a gradation value within a predetermined gradation range in the gradation image. The image evaluation apparatus according to any one of claims 1 to 4,
The calculating means calculates an absolute value of the difference between the image information acquired for each of a plurality of image portions having different gradation values from each other by a predetermined number in the gradation image, and is calculated for each predetermined gradation range. An image evaluation apparatus that calculates a difference between a maximum value and a minimum value of the absolute value and calculates an evaluation value of the gradation based on a magnitude of a difference between the maximum value and the minimum value . The image evaluation apparatus according to any one of claims 1 to 5,
An image evaluation apparatus using brightness as the image information used for calculating the evaluation value of the gradation. The image evaluation apparatus according to any one of claims 1 to 6,
An image evaluation apparatus using an evaluation value indicating a degree of graininess in the gradation image as the noise evaluation value. Storage means for storing image data of a multi-tone image;
In an image forming apparatus comprising: an image forming unit that forms an image based on the image data;
An image forming apparatus comprising the image evaluation apparatus according to claim 1. The image forming apparatus according to claim 8.
Image data processing means for correcting the image data of the multi-tone image to be image-formed based on the tone evaluation value corrected based on the noise evaluation value;
An image forming apparatus that forms the multi-tone image based on the image data after the correction. An image quality evaluation method for evaluating the image quality of a multi-tone image,
Obtaining gradation-related image information by measuring a gradation image whose gradation changes continuously;
Calculating a gradation evaluation value in a characteristic indicating a change in the image information with respect to a change in the gradation of the gradation image based on the image information of the gradation image;
Obtaining a noise evaluation value indicating the magnitude of noise in the gradation image;
And correcting the gradation evaluation value based on the noise evaluation value.