JP2005191890A - Image processing device, image processing method, image processing program, recording medium stored with image processing program and image forming apparatus with image processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor which can detect noise with pinpoint accuracy and can perform a noise removal without influencing adjoining pixels, and to provide an image processing method, an image processing program, a recording medium stored with the image processing program, and an image forming apparatus with the image processor. <P>SOLUTION: An image processor is provided with a data conversion means 141 converting input image data into lightness data and chromaticity data, a data addition means 142 outputting color image data in which pixel position information is added to the image data after the conversion, an image data classifying means 147 classifying the color image data into a plurality of color spaces, a distance calculation means 148 calculating relative distance information between pixels by the pixel position information, a noise detecting means 149 detecting a noise in the color image data by the classified color image data, the pixel position information and the relative distance information between pixels, and a noise removing means 144 removing the detected noise. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention particularly relates to an image processing apparatus, an image processing method, an image processing program, a recording medium on which an image processing program is recorded, and an image forming apparatus including the image processing apparatus.

  In recent years, digitalization of OA equipment has rapidly progressed, and the demand for image output has shifted from monochrome to color, and from analog to digital, so electrophotographic digital color copiers and inkjet / thermal transfer color. Printers and the like are widely used by general users. For example, image information input from an input device such as a digital camera or a scanner, or image information created on a computer is output from these output devices. Especially recently, there have been cases where digital cameras are connected directly to these output devices without going through a computer. In addition, even general users have been outputting color images with various printers and copiers. However, in this case, noise due to the characteristics of the imaging device or the like in the input device may be included. In some cases, a scanner, a copying machine, or the like includes unintended noise due to, for example, dirt on a glass surface when reading a document.

In such a case, noise reduction processing is performed. Conventionally, the reduction processing creates a histogram or the like based on the luminance information or density value information of the image, refers to it, and applies a smoothing filter. It has been performed by performing a smoothing process such as applying. In order to reduce color noise without causing deterioration of image brightness, a video signal processing method for applying a smoothing filter in the vertical direction to pigment data has been proposed (see, for example, Patent Document 1). Also, in order to reduce color noise at a high level without degrading the apparent resolution related to the color signal, color image data composed of a signal indicating brightness and a signal indicating color is input, and the brightness is An image processing method has also been proposed in which smoothing processing is performed on a signal indicating the color while holding a signal indicating the color (see, for example, Patent Document 2).
JP-A-5-153608 JP 2001-175843 A

  However, since the conventional processing method as described above performs the smoothing process, there is a problem that not only noise in the image but also its adjacent pixels are affected. Furthermore, there is a problem that as the number of times of the smoothing process is increased, the overall image becomes blurred.

  The present invention has been made in view of the above. In order to improve the accuracy of noise detection, the present invention focuses on positional information of an image, and as a result, noise can be detected accurately and pinpointly, and smoothing processing can be performed. Image processing apparatus, image processing method, image processing program, recording medium on which image processing program is recorded, and image forming apparatus provided with image processing apparatus that can perform noise removal that does not need to affect adjacent pixels The purpose is to provide.

  In order to achieve the above object, an image processing apparatus according to the present invention includes: data conversion means for converting input image data into brightness data information and chromaticity data information; and the brightness data information and the chromaticity data information. Data adding means for outputting color image data to which pixel position data information is added, and image data classification means for classifying the color image data into a plurality of color spaces based on the brightness data information and the chromaticity data information Distance calculating means for calculating relative distance information between pixels in the color image data based on the pixel position data information added by the data adding means; and the color image data classified by the image data classification means; Noise detection for detecting noise in the color image data based on the pixel position data information and the relative distance information between the pixels And the step, characterized in that it comprises a noise removing unit for removing the detected noise in said color image data in said noise detection means.

  Here, the brightness data information is, for example, brightness data information and luminance data information, but is not limited thereto.

  According to the image processing apparatus of the present invention, it is possible to improve the noise detection accuracy by considering the position information of the image in addition to the brightness data information such as the brightness data information and the brightness data information. As a result, noise can be detected accurately and pinpointed, and noise removal that does not affect adjacent pixels can be performed.

  In the image processing apparatus of the present invention, the image data classifying unit may reduce the color difference of the color image data within a color space constituted by the brightness data information and the chromaticity data information. It is good also as a characteristic to classify | categorize into a rectangular parallelepiped area so that it may become.

  According to the image processing apparatus of the present invention, the color image data is classified into a rectangular parallelepiped region so that the color difference in the region is small, and can be used as a guideline for subsequent noise detection.

  In the image processing apparatus according to the aspect of the invention, the noise detection unit may calculate a correlation with respect to the relative distance information between the pixels in the color image data classified by the image data classification unit, and perform correlation. It is good also as detecting noise by calculating | requiring.

  According to the image processing apparatus of the present invention, the noise detection accuracy is improved by calculating the frequency of the relative distance information between the pixels in the classified image data and further creating a histogram to obtain the correlation. It can be easily determined with a simple and simple circuit configuration.

  Further, in the image processing apparatus of the present invention, the noise removing unit retains the brightness data information for the image data determined to be noise by the noise detecting unit, and converts the brightness data information into the chromaticity data information. Alternatively, noise removal may be performed.

  Here, as specific noise removal processing, for example, for the target pixel determined to be noise by the noise detection unit, an average value of chromaticity data information of peripheral pixels existing around the target pixel However, the present invention is not limited to such a process. As the peripheral pixels, for example, four pixels above, below, left, and right of the target pixel, and eight neighboring pixels including pixels adjacent in an oblique direction are included. Further, when noise pixels are included in some of these peripheral pixels, for example, an average value may be obtained from the remaining peripheral pixels excluding such noise pixels.

  According to the image processing apparatus of the present invention, brightness data information such as brightness data information and brightness data information is held as it is when noise is removed. As a result, it is possible to perform noise removal processing without causing deterioration in luminance of the image. If the average value of the chromaticity data information of the surrounding pixels of the target pixel is obtained for the target pixel determined to be noise and replaced with the chromaticity data information of the target pixel, It is possible to easily perform noise removal processing without incurring luminance deterioration.

  Alternatively, the image processing method of the present invention includes a data conversion step of converting input image data into brightness data information and chromaticity data information, and pixel position data information in the brightness data information and the chromaticity data information. A data addition step for outputting the added color image data, an image data classification step for classifying the color image data into a plurality of color spaces based on the brightness data information and the chromaticity data information, and the data addition A distance calculation step of calculating relative distance information between pixels in the color image data based on the pixel position data information added in the step; the color image data classified in the image data classification step; and the pixel position data information And noise in the color image data is detected based on the relative distance information between the pixels. A noise detecting step, characterized in that it comprises a noise removing step for removing a noise of said noise detecting the in the color image data detected in the step.

  Here, the brightness data information is, for example, brightness data information and luminance data information, but is not limited thereto.

  According to the image processing method of the present invention, noise detection accuracy can be improved by taking into consideration the position information of the image in addition to the brightness data information such as the brightness data information and the brightness data information. As a result, noise can be detected accurately and pinpointed, and noise removal that does not affect adjacent pixels can be performed.

  Or the image processing program of this invention makes a computer perform the said image processing method, It is characterized by the above-mentioned.

  According to the image processing program of the present invention, the image processing method of the present invention can be realized anywhere as long as there is a computer environment capable of executing the program. Further, if this image processing program can be executed by a general-purpose computer, it is not necessary to prepare a dedicated computer environment for realizing the image processing method of the present invention. Usefulness increases.

  Or the recording medium which recorded the image processing program of this invention is a computer-readable recording medium, Comprising: The said image processing program is recorded, It is characterized by the above-mentioned.

  According to the recording medium on which the image processing program of the present invention is recorded, the image processing program of the present invention can be provided in a portable manner. In addition, the image processing method of the present invention can be easily realized in various places and environments, and the versatility of the image processing method of the present invention can be enhanced.

  Alternatively, an image forming apparatus according to the present invention includes any one of the image processing apparatuses described above.

  According to the image forming apparatus of the present invention, it is possible to provide an image forming apparatus capable of performing noise reduction processing with high accuracy without causing deterioration in luminance of an image by considering image position information for noise detection. be able to.

  According to the image processing apparatus or the image processing method of the present invention, it is possible to improve noise detection accuracy by considering the position information of the image in addition to the brightness data information such as the brightness data information and the luminance data information. As a result, noise can be detected accurately and pinpointed, and noise removal that does not affect adjacent pixels can be performed.

  Further, according to the image processing program of the present invention, the image processing method of the present invention can be realized anywhere as long as there is a computer environment capable of executing the program. Further, if this image processing program can be executed by a general-purpose computer, it is not necessary to prepare a dedicated computer environment for realizing the image processing method of the present invention. Usefulness increases.

  Further, according to the recording medium on which the image processing program of the present invention is recorded, the image processing program of the present invention can be provided in a portable manner. In addition, the image processing method of the present invention can be easily realized in various places and environments, and the versatility of the image processing method of the present invention can be enhanced.

  In addition, according to the image forming apparatus of the present invention, an image forming apparatus that can perform noise reduction processing with high accuracy without causing deterioration in luminance of an image by considering image position information for noise detection. Can be provided.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<First Embodiment>
FIG. 1 is a block diagram showing a configuration of a digital color copying machine 100 including a color image processing apparatus 1 according to the first embodiment of the present invention.

  As shown in FIG. 1, the color image processing apparatus 1 includes an A / D conversion unit 10, a shading correction unit 11, an input tone correction unit 12, a region separation processing unit 13, a noise removal processing unit 14, a color correction unit 15, It comprises a black generation and under color removal unit 16, a spatial filter processing unit 17, an output tone correction unit 18, and a tone reproduction processing unit 19, which include a color image input device 2, a color image output device 3, and the like. Are connected to form a digital color copying machine 100 as a whole.

  The color image input device 2 (image reading means) is composed of, for example, a scanner unit having a CCD (Charge Coupled Device), and the reflected light image from the original is converted into RGB (R: red, G: green, B: blue). The analog signal is read by the CCD and input to the color image processing apparatus 1.

  As shown in FIG. 1, the analog signal read by the color image input device 2 is output to the color image processing device 1. In the color image processing device 1, an A / D conversion unit 10, a shading correction unit 11, Input tone correction unit 12, area separation processing unit 13, noise removal processing unit 14, color correction unit 15, black generation and under color removal unit 16, spatial filter processing unit 17, output tone correction unit 18, and tone reproduction processing The images are sent in the order of the unit 19 and output to the color image output device 3 as CMYK digital color signals.

  The A / D (analog / digital) converter 10 converts RGB analog signals into digital signals.

  The shading correction unit 11 performs processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the color image input apparatus 2 on the digital RGB signal sent from the A / D conversion unit 10. Is.

  The input tone correction unit 12 adjusts the color balance for the RGB signal (RGB reflectance signal) from which various distortions have been removed by the shading correction unit, and at the same time, is used in the color image processing apparatus 1 such as a density signal. The signal is converted into an easy-to-handle signal of the image processing system.

  The region separation processing unit 13 separates each pixel in the input image into one of a character region, a halftone dot region, and a photograph region from the RGB signal. Based on the separation result, the region separation processing unit 13 sends a region identification signal indicating to which region the pixel belongs to the black generation and under color removal unit 16, the spatial filter processing unit 17, and the gradation reproduction processing unit 19. In addition to the output, the input signal output from the input tone correction unit 12 is directly output to the subsequent noise removal processing unit 14.

The noise removal processing unit 14 removes noise in the input image from the RGB signals. The noise removal processing unit 14 converts the input data output from the region separation processing unit 13 into, for example, CIEL ^* a ^* b ^* (CIE: Commission International de l'Eclairage: International Lighting Commission. L ^* : brightness, a ^*. The color space is converted into a luminance color difference separation type color space such as b ^* : chromaticity), but is not limited to CIEL ^* a ^* b ^* . Next, noise removal processing is performed, and the data after the removal processing is output as it is to the subsequent color correction unit 15.

  The color correction unit 15 performs processing for removing color turbidity based on the spectral characteristics of CMY (C: cyan, M: magenta, Y: yellow) color materials including unnecessary absorption components in order to realize faithful color reproduction. Is. Furthermore, in the image processing apparatus 1 of the present invention, the color correction unit 15 can perform image information modification processing.

  The black generation and under color removal unit 16 generates black (K) signals from the CMY three-color signals after color correction, and subtracts the K signals obtained by black generation from the original CMY signals to generate new CMY signals. The CMY three-color signal is converted into a CMYK four-color signal.

  As an example of the black generation process, there is a method (general method) for generating black by skeleton black. In this method, the input / output characteristic of the skeleton curve is y = f (x), the input data is C, M, Y, the output data is C ′, M ′, Y ′, K ′, UCR (Under Color Assuming that the (removal) rate is α (0 <α <1), the black generation and under color removal processing is expressed by the following Equation 1.

空間フィルタ処理部１７は、黒生成下色除去部１６より入力されるＣＭＹＫ信号の画像データに対して、領域識別信号を基にデジタルフィルタによる空間フィルタ処理を行い、空間周波数特性を補正することによって出力画像のぼやけや粒状性劣化を防ぐように処理するものであって、階調再現処理部１９も、空間フィルタ処理部１７と同様に、ＣＭＹＫ信号の画像データに対して、領域識別信号を基に所定の処理を施すものである。

The spatial filter processing unit 17 performs spatial filter processing using a digital filter on the image data of the CMYK signal input from the black generation and under color removal unit 16 based on the region identification signal, thereby correcting the spatial frequency characteristics. The gradation reproduction processing unit 19 performs processing so as to prevent blurring of the output image and deterioration of graininess. Similarly to the spatial filter processing unit 17, the tone reproduction processing unit 19 also uses a region identification signal based on the image data of the CMYK signal. Is subjected to predetermined processing.

  For example, the region separated into characters by the region separation processing unit 13 has a high frequency enhancement amount in the sharp enhancement processing in the spatial filter processing by the spatial filter processing unit 17 in order to improve the reproducibility of black characters or color characters in particular. Increased. At the same time, the gradation reproduction processing unit 19 selects binarization or multi-value processing on a high-resolution screen suitable for high frequency reproduction.

  Further, with respect to the region separated into halftone dots by the region separation processing unit 13, the spatial filter processing unit 17 performs low-pass filter processing for removing the input halftone component. The output tone correction unit 18 performs output tone correction processing for converting a signal such as a density signal into a halftone dot area ratio which is a characteristic value of the color image output device 3, and then the tone reproduction processing unit 19. Then, gradation reproduction processing (halftone generation) is performed so that the image is finally separated into pixels and each gradation is reproduced. For the region separated into photographs by the region separation processing unit 13, binarization or multi-value processing is performed on the screen with an emphasis on gradation reproducibility.

  The image data subjected to the above-described processes is temporarily stored in a storage unit (not shown), read out at a predetermined timing, and input to the color image output device 3.

  The image output device 3 outputs image data onto a recording medium (for example, paper). For example, a color image output device using an electrophotographic method or an ink jet method can be used, but the image output device 3 is particularly limited. It is not a thing.

Further, when the image output device 3 is configured by a display device such as a CRT or a liquid crystal display, the black generation and under color removal unit 16 in FIG. 1 is unnecessary, and the color correction unit 15 changes from L ^* a ^* b ^{* to} RGB. Conversion is performed.

  The above processing is controlled by a CPU (Central Processing Unit) (not shown).

  FIG. 2 is a block diagram of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention. FIG. 3 is a flowchart showing an image data processing procedure in the noise removal processing unit 14. FIG. 4 is an example of color image data to which position information is added. FIG. 5 is an example of the size of a region (cuboid) classified by the image data classification unit 147 of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention.

As shown in FIG. 2, the noise removal processing unit 14 includes an L ^* a ^* b ^* conversion unit 141 (data conversion unit), a pixel position information addition unit 142 (data addition unit), and L ^* , a ^* , b. ^* , X, y branching unit 143, image data classifying unit 147 (image data classifying unit), relative distance calculating unit 148 (distance calculating unit), noise detecting unit 149 (noise detecting unit), and noise removing unit 144 (Noise removal means), a noise removal completion confirmation unit 145, and a pixel position information removal unit 146 are provided, and noise removal processing is performed by these units.

  Next, image data processing by the noise removal processing unit 14 will be described with reference to FIGS.

When the image data processing is started, first, the color image data composed of RGB input to the L ^* a ^* b ^* conversion unit 141 is converted into the L ^* a ^* b ^* color system (step S1). Here, L ^* , a ^* , and b ^* are spatial coordinates in the uniform color space of the L ^* a ^* b ^* color system (CIE1976).

Next, in the pixel position information adding unit 142, position information (see FIG. 4) represented by two-dimensional orthogonal coordinates is added to all the pixels of the L ^* a ^* b ^* data converted in step S1, The data is sent to the L ^* , a ^* , b ^* , x, y branching unit 143 (step S2). From the L ^* , a ^* , b ^* , x, y branching unit 143, L ^* , a ^* , b ^* , x, y information is sent to the image data classifying unit 147, and to the noise removing unit 144. The a ^* , b ^* , x, and y information is sent, and the L ^* information is sent to the noise removal completion confirmation unit 145.

In the image data classifying unit 147, based on the information of L ^* , a ^* , b ^* sent from the L ^* , a ^* , b ^* , x, y branching unit 143, the color image data in the area to be classified By classifying the color difference to be small (step S3), it can be used as a guideline for subsequent noise detection. For example, the size of the area to be classified or the position of the area may be determined as a fixed value in advance, or may be set separately later. The area is, for example, the width of L ^* , a ^* , b ^* values,
L ^* Value range = 2
a ^* Value range = 5
b ^* Value range = 5
There is a method of classifying by all the data included in the rectangular parallelepiped 20 as shown in FIG.

In the relative distance calculation unit 148, among the classified L ^* , a ^* , b ^* , x, y information sent from the L ^* , a ^* , b ^* , x, y branching unit 147, the position information x The relative distance r between the pixels is calculated from the information of y and y, and the value is transmitted to the noise detection unit 149 together with the position information (step S4).

  The noise detection unit 149 creates a histogram based on the correlation information obtained by the relative distance calculation unit 148 to obtain the correlation. Based on the correlation state, noise is detected by determining whether or not it is noise (step S5). If it is determined that the noise is present, noise information such as pixel position information where the noise exists is transmitted to the noise removing unit 144. Details of the noise determination method will be described later with reference to FIGS.

In the noise removing unit 144, the noise information inputted from the noise detection unit ^{149, L *, a *,} b *, x, a sent from the y branch unit 143 ^*, b ^*, x, the information of y groups Then, a noise removal process is performed (step S6). The details of the noise removal method will be described later with reference to FIGS.

The noise removal completion confirmation unit 145 confirms whether or not the series of noise removal processes described above has been completed (step S7). If the completion is not confirmed, the process returns to the noise detection of step S5 again. If the completion is confirmed, the data L ^* sent from the L ^* , a ^* , b ^* , x, y branching unit 143 is added. It is transmitted to the pixel position information removing unit 146.

The pixel position information removal unit 146 removes the x and y information from the L ^* , a ^* , b ^* , x, and y information input from the noise removal completion confirmation unit 144 (step S8), and the color image data becomes L ^*. , A ^* , b ^* information are processed.

  This is the end of the series of noise removal processes.

-About the noise judgment method in the noise detection part 149-
FIG. 6 is a distribution example on the pixel positions of the same classified data group classified by the image data classification unit 147 of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention. Shows case 1 and (b) shows case 2. FIG. 7 is an example of a histogram diagram created in case 1 by the noise detection unit 149 of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention. A shows when A is the starting point, (b) shows when the representative point B is the starting point, and (c) shows when the representative point C is the starting point. FIG. 8 is an example of a histogram diagram created in case 1 by the noise detection unit 149 of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention. P shows the time when the starting point is reached, (b) shows the time when the representative point Q is the starting point, and (c) shows the time when the representative point R is the starting point. FIG. 9 is an example of a histogram diagram created in case 2 by the noise detection unit 149 of the noise removal processing unit 14 of the color image processing apparatus 1 according to the first embodiment of the present invention. The representative point S is the starting point. Showing the time.

  6A and 6B are two examples of distributions on the pixel positions of the same classified data group classified by the image data classification unit 147 (see FIG. 2). Each case in the figure shows the following conditions.

  Case 1: The color information of a region occupying a relatively large area in the image and the scattered noise are the same color.

  Case 2: There are many scattered noises of the same color.

The determination of noise is made based on whether a histogram is created starting from a certain point and both of the following conditions (1) and (2) are satisfied. That is, when both of these conditions are satisfied, it is determined that the starting point is noise. Note that R _area and R _freq are values of the portions illustrated in FIGS. 8A to 8C, respectively.

(1) The _area indicated by R _area is equal to or greater than the threshold (2) The frequency indicated by R _freq is equal to or less than the threshold In the above condition (1), when the area is equal to or greater than the threshold, the pixel at the start point of the histogram is It is isolated (positionally distant) and is a condition for determining noise.

  In the above condition (2), when the frequency is equal to or less than the threshold value, it indicates that the number of pixels adjacent to the pixel at the start point of the histogram is small, and that a configured cluster is small. Therefore, this is one condition for determining that the noise is present.

Here, the threshold value of R _area is set to be about twice the noise size, for example. For example, in the case of 2 pixels × 2 pixels (4 pixels), the noise size is set to “8” (equivalent to twice the 4 pixels). This threshold value can be freely reset separately, and is not limited to this value. Further, the threshold value of R _freq is naturally determined by the set noise size. For example, if the noise size is 2 pixels × 2 pixels (4 pixels), the threshold value is “3” (corresponding to 4 pixels−1), and if the noise size is 3 pixels × 3 pixels (9 pixels), the threshold value is “3”. 8 "(corresponding to 9 pixels-1).

  Examining whether or not the above condition is satisfied in FIGS. 7 to 9, since none of the above conditions (1) is satisfied in FIGS. 7A to 7C, the representative points A, B, and C are Neither is judged as noise. 8A to 8C both satisfy the above conditions (1) and (2), and the representative points P, Q, and R are all determined to be noise. In FIG. 9, both of the above conditions (1) and (2) are also satisfied, and the representative point S is determined to be noise.

-About the noise removal processing method in the noise removal part 144-
FIG. 10 is a diagram showing the relationship between noise pixels and pixels in the vicinity of the surrounding 8 during the noise removal processing by the color image processing apparatus 1 according to the first embodiment of the present invention, and FIG. It is a figure which shows the relationship with 4 pixels. The noise pixel indicates a pixel that is determined as noise by the noise detection unit 149.

For pixels judged as noise as described above, a ^* of the pixel, b ^* a ^* near pixels instead of the value to remove noise by replacing the average value of b ^* values. At this time, L ^* is kept as it is.

As shown in FIG. 10, when 8 neighboring pixels are used as peripheral pixels, first, the a ^* and b ^* values of the 8 neighboring pixels of the noise pixel are searched based on the pixel position information accompanying the noise information. To do. Therefore, the values near 8 for the a ^* and b ^* values are averaged, and the result is used as the a ^* and b ^* values of the noise pixel.

As shown in FIG. 11, in the case where four pixels are used as peripheral pixels, similarly, the a ^* and b ^* values of the four pixels above, below, left, and right of the noise pixel are first based on the positional information accompanying the noise information. Search for. Therefore, the a ^* and b ^* values are averaged for the upper, lower, left and right four pixels, respectively, and the result is used as the noise pixel a ^* and b ^* values.

In any case, if the surrounding pixels also contain noise pixels, the values of the pixels are excluded, and the values of the remaining pixels are averaged to obtain the a ^* and b ^* values. .

According to the configuration of the first embodiment described above, in addition to the L ^* , a ^* , and b ^* values of each pixel, the positional information x and y values of each pixel and the correlation distance r between the pixels are considered. This makes it possible to accurately and pinpoint noise detection. Also, noise processing is performed by replacing the a ^* and b ^* values with the average value of the a ^* and b ^* values of the surrounding pixels only for the noise pixels detected in this way. As a result, the L ^* value of the noise pixel is maintained as it is and does not deteriorate, and the L ^* , a ^* , and b ^* values of the surrounding pixels are not affected at all.

Second Embodiment
In the second embodiment of the present invention, noise of achromatic color such as gray can be removed by using the information of L ^* . Since the second embodiment is the same as the first embodiment except for the points described below, the same constituent members will be denoted by the same reference numerals, and only differences will be described.

  FIG. 12 is a block diagram of the noise removal processing unit 14a of the color image processing apparatus 1 according to the second embodiment of the present invention. The configuration of the color image processing apparatus 1 is different only in that the noise removal processing unit 14 in the first embodiment described with reference to FIG. 1 is replaced with a noise removal processing unit 14a. The configuration of the noise removal processing unit 14a is the same as that of the noise removal processing unit 14 of the first embodiment except for the points described below.

As shown in FIG. 12, the L ^* , a ^* , b ^* , x, y branching unit 143a also sends the L ^* information together with the a ^* , b ^* , x, y information to the noise removing unit 144a. By using this L ^* information, the noise removal unit 144a can perform noise removal processing even when the corresponding noise is an achromatic color such as gray (a ^* , b ^* ≈0), for example.

  FIG. 13 is a diagram showing the relationship between a noise pixel and its neighboring 8 neighboring pixels during noise removal processing by the color image processing apparatus according to the second embodiment of the present invention, and FIG. It is a figure which shows the relationship with a pixel.

For pixels judged as noise as described above, the pixel L ^*, a ^*, b ^* of the surrounding pixels instead of the value L ^*, a ^*, removes noise by replacing the average value of b ^* value To do.

As shown in FIG. 13, in the case where 8 neighboring pixels are used as the peripheral pixels, first, based on the pixel position information accompanying the noise information, the L ^* , a ^* , b ^* values of the 8 neighboring pixels of the noise pixel. Search for. Therefore, the L ^* , a ^* , and b ^* values are averaged around 8 values, and the result is used as the L ^* , a ^* , and b ^* values of the noise pixel.

As shown in FIG. 14, in the case where four pixels are used as peripheral pixels, similarly, first, L ^* , a ^* , b of the four pixels above, below, left, and right of the noise pixel are based on the positional information accompanying the noise information. ^* Search for a value. Therefore, the L ^* , a ^* , and b ^* values are averaged for the four pixels in the vertical and horizontal directions, and the result is used as the L ^* , a ^* , and b ^* values of the noise pixel.

In any case, if the surrounding pixels include noise pixels, the values of the pixels are excluded, the values of the remaining pixels are averaged, and the result is L ^* , a ^* , b ^* Value.

According to the second embodiment described above, the L ^* with respect to only the detected noise pixel, a ^*, b ^* values of the surrounding pixels L ^*, a ^*, the mean value of b ^* value Noise processing is performed by replacement. This makes it possible to perform appropriate noise removal processing even in the case of achromatic noise such as gray (a ^* , b ^* ≈0).

<Embodiment as Program and Recording Medium>
The image processing methods described in the first and second embodiments described above can be realized as an image processing program that can be executed by a computer. For example, the image processing program may be executed by a microprocessor built in the digital color copying machine as described above. Alternatively, it may be incorporated in a printer driver such as a personal computer, or may be incorporated as a function such as an image processing application program.

  Such an image processing program may be recorded on a computer-readable recording medium.

  As a result, the recording medium on which the image processing program of the present invention is recorded can be provided in a portable manner.

  In the present embodiment, as the recording medium, a memory (not shown) such as a ROM itself may be a program medium because processing is performed by a microcomputer. Although not shown, a program reading device may be provided as an external storage device, and the program medium may be read by inserting a recording medium therein.

  In any case, the stored program may be configured to be accessed and executed by the microprocessor, or in any case, the program is read and the read program is illustrated in the microcomputer. The program may be downloaded to a non-program storage area and executed. It is assumed that this download program is stored in the main device in advance.

  Here, the program medium is a recording medium configured to be separable from the main body, such as a tape system such as a magnetic tape or a cassette tape, a magnetic disk such as a flexible disk or a hard disk, a CD-ROM / MO / MD / DVD, or the like. Semiconductors such as optical discs, IC cards (including memory cards) / optical cards, etc., mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash ROM, etc. It may be a medium that carries a fixed program including a memory.

  In the present embodiment, since the system configuration is connectable to a communication network including the Internet, the medium may be a medium that fluidly carries the program so as to download the program from the communication network. When the program is downloaded from the communication network in this way, the download program may be stored in the main device in advance or installed from another recording medium.

  The above-described image processing method is executed by reading the recording medium by a program reading device provided in a digital color copying machine or a computer system.

  The present invention can be implemented in various other forms without departing from the spirit or main features thereof. Therefore, the above-mentioned embodiment is only a mere illustration in all points, and should not be interpreted limitedly. The scope of the present invention is indicated by the claims, and is not restricted by the text of the specification. Further, all modifications and changes belonging to the equivalent scope of the claims are within the scope of the present invention.

1 is a block diagram illustrating a configuration of a digital color copying machine including a color image processing apparatus according to a first embodiment of the present invention. 2 is a block diagram of a noise removal processing unit of the color image processing apparatus according to the first embodiment of the present invention. FIG. It is a flowchart which shows the image data processing procedure in the noise removal process part of the color image processing apparatus which concerns on 1st Embodiment of this invention. It is an example of color image data to which position information is added. It is a figure which shows the structure of the color image data which added the positional information used by this invention. It is an example of the magnitude | size of the area | region (cuboid) classified in the image data classification | category part of the noise removal process part of the color image processing apparatus which concerns on 1st Embodiment of this invention. It is a distribution example on the pixel position of the same classification data group classified in the image data classification part of the noise removal processing part of the color image processing device concerning a 1st embodiment of the present invention, (a) shows case 1, (B) shows Case 2. It is an example of the histogram figure produced in the case of case 1 in the noise detection part of the noise removal process part of the color image processing apparatus which concerns on 1st Embodiment of this invention, (a) is when the representative point A is a starting point. (B) shows when the representative point B is the starting point, and (c) shows when the representative point C is the starting point. It is an example of the histogram figure produced in the case of case 1 in the noise detection part of the noise removal process part of the color image processing apparatus which concerns on 1st Embodiment of this invention, (a) is when the representative point P is a starting point. (B) shows when the representative point Q is the starting point, and (c) shows when the representative point R is the starting point. It is an example of the histogram figure produced in the case of case 2 in the noise detection part of the noise removal process part of the color image processing apparatus which concerns on 1st Embodiment of this invention, and the time when the representative point S is a starting point is shown. It is a figure which shows the relationship between the noise pixel at the time of the noise removal process by the color image processing apparatus which concerns on 1st Embodiment of this invention, and the pixel of the periphery 8 vicinity. It is a figure which shows the relationship between the noise pixel at the time of the noise removal process by the color image processing apparatus which concerns on 1st Embodiment of this invention, and its upper, lower, left, and right 4 pixels. It is a block diagram of the noise removal process part of the color image processing apparatus which concerns on 2nd Embodiment of this invention. It is a figure which shows the relationship between the noise pixel at the time of the noise removal process by the color image processing apparatus which concerns on 2nd Embodiment of this invention, and the pixel of the periphery 8 vicinity. It is a figure which shows the relationship between the noise pixel at the time of the noise removal process by the color image processing apparatus which concerns on 2nd Embodiment of this invention, and its upper, lower, left, and right 4 pixels.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Color image processing apparatus 2 Color image input apparatus 3 Color image output apparatus 10 A / D conversion part 11 Shading correction part 12 Input gradation correction part 13 Area separation processing part 14, 14a Noise removal processing part 141 L ^* a ^* b ^* Conversion unit 142 Pixel position information addition unit 143, 143a L ^* , a ^* , b ^* , x, y branching unit 144, 144a Noise removal unit 145 Noise removal completion confirmation unit 146 Pixel position information removal unit 147 Image data classification unit 148 Relative Distance calculation unit 149 Noise detection unit 15 Color correction unit 16 Black generation and under color removal unit 17 Spatial filter processing unit 18 Output tone correction unit 19 Tone reproduction processing unit 100 Digital color copying machine

Claims (13)

Data conversion means for converting input image data into brightness data information and chromaticity data information;
Data adding means for outputting color image data obtained by adding pixel position data information to the brightness data information and the chromaticity data information;
Image data classification means for classifying the color image data into a plurality of color spaces based on the brightness data information and the chromaticity data information;
Distance calculation means for calculating relative distance information between pixels in the color image data based on the pixel position data information added by the data addition means;
Noise detection means for detecting noise in the color image data based on the color image data classified by the image data classification means, the pixel position data information, and the relative distance information between the pixels;
An image processing apparatus comprising: noise removal means for removing noise in the color image data detected by the noise detection means.   The image data classifying unit classifies the color image data into a rectangular parallelepiped region so that a color difference in the region is small in a color space constituted by the brightness data information and the chromaticity data information. The image processing apparatus according to claim 1.   The noise detecting means detects noise by calculating a frequency and obtaining a correlation with respect to relative distance information between the pixels in the color image data classified by the image data classifying means. The image processing apparatus according to claim 1.   The noise removing unit performs noise removal on the chromaticity data information while holding the brightness data information for the image data determined to be noise by the noise detecting unit. The image processing apparatus according to claim 1, wherein:   The noise removing unit obtains an average value of chromaticity data information of peripheral pixels existing around the target pixel with respect to the target pixel determined to be noise by the noise detection unit, and calculates the color of the target pixel The image processing apparatus according to claim 4, wherein the image processing apparatus is replaced with degree data information.   The image processing apparatus according to claim 1, wherein the brightness data information is brightness data information.   The image processing apparatus according to claim 1, wherein the brightness data information is luminance data information. A data conversion step of converting input image data into brightness data information and chromaticity data information;
A data addition step of outputting color image data obtained by adding pixel position data information to the brightness data information and the chromaticity data information;
An image data classification step for classifying the color image data into a plurality of color spaces based on the brightness data information and the chromaticity data information;
A distance calculating step of calculating relative distance information between pixels in the color image data based on the pixel position data information added in the data adding step;
A noise detection step of detecting noise in the color image data based on the color image data classified in the image data classification step, the pixel position data information, and the relative distance information between the pixels;
An image processing method comprising: a noise removal step of removing noise in the color image data detected in the noise detection step.   9. The image processing method according to claim 8, wherein the brightness data information is brightness data information.   9. The image processing method according to claim 8, wherein the brightness data information is luminance data information.   An image processing program for causing a computer to execute the image processing method according to any one of claims 8 to 10.   The computer-readable recording medium which recorded the image processing program of Claim 11. An image forming apparatus comprising the image processing apparatus according to claim 1.

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