JP2003110861A - Method and device for tone reproduction of color gradation image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and a device for tone reproduction capable of obtaining smooth property of gradation simultaneously with fine color reproduction in the binary coding of a color gradation image. SOLUTION: The tone reproducing device is provided with error diffusion processing units, dot number operating units, dot number correcting units, and binary coding control units. The error diffusion processing unit is provided with a correcting input data buffer for temporarily retaining the correcting input data with respect to a conventional error diffusion process and whose number of set is corresponding to the number of color planes of a color image to be processed. The dot number operating unit operates the number of dot for reproducing the image from the inputted color data. The dot number correcting unit corrects the dot number operated by the dot number operating unit employing a fraction. The binary coding control unit grades the order of generation of dot of respective colors from the dot number operated by the dot number operating unit and the values of respective colors of the input color data, further, prohibits the generation of dot forcibly in the binary coding unit with respect to a color dot, decided that a dot is not generated.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a binarizing method and apparatus for converting a color gradation image into binary.

[0002]

2. Description of the Related Art In color printers, there is a printer in which pixels of each ink color are represented by ON / OFF of dots, that is, by binary representation. For example, it is an electrophotographic or inkjet color printer. These printers usually use three color inks, cyan (C), magenta (M), and yellow (Y). By overlapping these three colors, C + M is red (R), C + Y
It is possible to create dots of green (G), blue (B) of Y + M, and black (K) of C + M + Y. By appropriately arranging the dots of these colors on the paper, a color mixture of the dots occurs in the eyes of the observer, and an intermediate color other than the above-mentioned dot colors can be reproduced.

On the other hand, many natural images and computer graphic images handled on a computer often have continuous gradation data. These are first RG
It is composed of primary color data such as B and CMY, and each primary color data is composed of continuous values. Specifically, assuming that the data of each primary color uses 8 bits per pixel, this pixel can take 256 values from 0 to 255.

When such an image is printed by the binary printer, it is necessary to convert 256 values for each ink color into binary values of ON / OFF, that is, binarize. In the binarization process, for example, 128, which is an intermediate value between 0 and 255, can be used as a threshold value, and ON / OFF of the dot can be determined based on the magnitude relationship with the threshold value. However, such a simple method cannot reproduce the continuous gradation of the original image, resulting in a result that is considerably inferior to a natural image having many continuous gradations.

Therefore, a pseudo halftone process is used which is capable of reproducing continuous gradations as they are while binarizing them. This is a method of artificially reproducing continuous gradations by devising the arrangement of dots.

There is an error diffusion method as one of pseudo halftone processing. The error diffusion method is a method in which, when binarizing multi-valued input image data, an error occurring before and after binarization is diffused to subsequent error data based on a ratio by a weighting coefficient. According to the error diffusion method, since the error of the gradation generated at the time of binarization is diffused to the surrounding pixels to eliminate the error, the reproducibility of the continuous gradation image is improved.

FIG. 5 is a block diagram showing the basic configuration of the error diffusion method. The correction value ME is added to the input image data IN of a specific pixel (target pixel) to correct it to obtain the correction input data MI, and the correction input data MI obtained by the addition unit 6 The binarization unit 7 that binarizes by a threshold value, the error calculation unit 8 that calculates the error ER between the corrected input data MI and the binary data BI for the pixel of interest, and the error calculation unit 8 An error diffusion unit 9 that diffuses the error ER to the surrounding pixels based on a weighting coefficient set in advance for unprocessed pixels located around the target pixel, and an error determined by the error diffusion unit 9 It comprises an error memory 10 which accumulates for each pixel and then transfers the accumulated error as a correction error to the adder unit 6.

The binarization by the error diffusion method will be described below. Here, the input color data is for one color (single color) of a plurality of color data,
By repeating this independently for each color, binarization of the entire color image data is achieved.

First, for the pixel of interest, the correction error ME stored in the error memory 10 is added to the input color data IN of a single color by the adder 6 to obtain corrected input data MI. For the correction input data MI, the binarization unit 7 sets the correction input data MI to one threshold value, for example, 12 which is an intermediate value between 0 and 255.
Binarization is performed with 8 as a threshold. That is, the binarization unit 7
When the input correction data is less than 128, the binary data is set to 0 (dot OFF), and when the input correction data is 128 or more, the binary data is set to 1 (dot ON). And Here, the input image data IN is represented by 0 to 255, whereas the correction input data MI has a correction value ME added to the input image data. Sometimes it exceeds 255. The post-binarization error calculation unit 8 calculates the difference between the corrected input data MI and the binary data BI as an error ER. In the error diffusion unit 9, the calculated error ER is calculated as a value to be diffused for each peripheral pixel based on a preset weighting coefficient for unprocessed pixels located around the target pixel. The calculated diffusion error for each surrounding pixel is accumulated in the error memory 10 for each pixel.

Explaining with a specific example of the weighting factor, in the error diffusion unit 9 of FIG.
The range of unprocessed surrounding pixels that diffuse the error ER is A, B,
If there are 6 pixels of C, D, E, and F, the pixel A?
The weighting factors for F are, for example, WA = 3, WB = 1, WC
= 1, WD = 3, WE = 1, WF = 1. When the weighting coefficient is generally Wi and the total weighting coefficient is Sw, the diffusion error of each pixel is Wi / Sw ×
Become ER. Here, the reason why the total of the weighting factors is divided by Sw is to normalize the diffusion error.

The above process is sequentially performed for each pixel, and one screen is processed. By such processing, the dots are arranged almost randomly, and the dots are arranged at a density according to the density, and as a result, pseudo and smooth gradation reproduction can be obtained.

For a color image, the binarization process is performed for each color plane. For example, if the input image is CMY
If it is an image, the above 2 for each plane of C, M and Y.
The binarization process is performed, and finally each is overlaid to form a color image. If it is an RGB image, the binarization processing is performed on each of the R, G, and B planes, and finally the respective planes are superimposed to form a color image. Here, when printing with a color printer using C, M, and Y inks,
For example, printing is performed by performing inversion processing such as R → C, G → M, and B → Y.

[0013]

By the way, in a color printer of an electrophotographic type or an ink jet type which is a binary printer, in order to reproduce a color, the toner or ink of the primary colors of the color is superposed to reproduce the color. When the binarization processing is independently performed on each color plane as described above, each color dot is generated irrespective of each other, and thus the dot generation positions are stochastically distributed. That is, of the reproduced colors, for example, when the original image data is a light red that is expressed as Y = M = 50%, Y = 50% and M = 50% monochromatic images are independently generated. Since the binarization processing is performed, Y and M dots are randomly generated in each of the Y and M planes. Therefore, in the finally reproduced image,
The Y dots, the M dots, and the R dots in which Y and M overlap each other are stochastically distributed.

However, a dot in which two inks overlap each other, such as an R dot, tends to have a murky color due to subtractive color mixture and a decrease in saturation. When it is desired to reproduce as vividly as possible, Y and M overlap. It is better to reduce the R dots and arrange the Y and M dots side by side to perform color reproduction. The above is the case of Y and M, but the same applies to other color combinations.

However, as described above, since the error diffusion method performs binarization processing independently for each color plane, it cannot be processed in consideration of the arrangement of dots between color planes, and the subtraction method described above is used. There is a problem that it is not possible to perform processing to reduce the mixed color dots as much as possible.

[0016]

In order to achieve the main object, a binarizing method for converting a color gradation image into a binary value according to the present invention is a binary gradation method of input data of the color gradation image. When the gradation is converted and reproduced in a pseudo manner, the error of the gradation between the data before and after the binarization is corrected data based on a predetermined weighting coefficient, and a plurality of consecutively input data is input. A method of reproducing a gradation of a color gradation image by an error diffusion method for binarizing the correction input data by diffusing it to the subsequent input image data, and temporarily storing the correction input data. The number of dots for reproducing the pixel can be calculated from the input color data, and the number of dots for reproducing the pixel can be calculated in parallel from the input color data. Dot number And the dot generation order of each color is ranked from the value of each color of the input color data, and for the color dots determined not to generate dots, the todd is not forcibly generated during binarization. Further, with respect to the calculated dot number, a fraction with respect to the input color data is temporarily held, and correction is performed by using the fraction when calculating the dot number in the subsequent pixel processing.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of a color gradation image binarizing method and apparatus of the present invention will be described below with reference to the drawings.

1 to 4 of the color gradation image of the present invention.
1 shows an embodiment of a quantizer.

Before explaining the binarization apparatus of this embodiment,
An image processing system including a part of the binarization device of this embodiment will be described.

As shown in FIG. 2, the image processing system includes a host computer 1 and a printer 2 connected to the host computer 1. Here, the host computer 1 transfers the original image data to the printer 2.

The original image data transferred from the host computer 1 is, for example, image data read by an image scanner (not shown), image data stored in the storage means of the host computer 1, or the host computer 1. There is image data such as artificially created computer graphics.

The printer 2 is the host computer 1
Input the original image data from
Image data input means 3 expressing multi-gradation image data (input image data) such as a value (0 to 255) and the image data transferred from the image data input means 3 are inputted, and binary data ( Here, the color is converted into white [0] and black [1]), and the gradation reproduction processing means 4 of this embodiment is used.
And a binary data printing means 5 for printing (gradation reproduction) based on the binary data output from the gradation reproduction processing means 4.

The structure of the gradation reproduction processing means 4 is shown in FIG. The binarization processing unit 15 of FIG. 3 is obtained by adding a correction input value buffer that temporarily holds the correction input value MI obtained by the addition unit 6 to the binarization processing unit of FIG. There is. Further, a dot number calculation unit 12, a binarization control unit 13, and a dot number correction unit 14 are arranged outside the binarization processing unit 15 so as to correspond to processing for input data of other colors. These will be described with reference to FIG.

An example of an embodiment of the present invention is shown in FIG. In the present embodiment, the input color image is made up of three colors of C, M, and Y, and correspondingly, the binarization processing units 15 are arranged in parallel corresponding to each color. The input image data of three colors is input to the dot number calculation unit 12 in addition to the binarization processing unit 15 corresponding to each color data. In the dot number calculation unit 12, from the color image data of the input pixel and the data of the dot number correction unit 14,
The number of dots used to reproduce the pixel is calculated. The binarization control unit 13 uses the number of dots calculated by the dot number correction unit 14 and the correction input data of each color held in the correction input value buffer 11 of the binarization processing unit 15 for each color to output each color. The priority order of the reproduced dots is determined, and the binarization unit 7 of the binarization processing unit 15 corresponding to each color is controlled to forcibly perform / do not perform binarization.

The operation of the gradation reproduction processing means 4 configured as described above will be described below with reference to the block diagrams of FIGS. 1 and 2 and the flowchart of FIG. Here, it is assumed that the input image data has three colors of C, M, and Y. In the case of a color image as described above, in a normal binarization process, for each plane of each color, that is, in the case of the above example, first, one plane of C data is binarized, and then M data is set to one. The plane is binarized, and then the Y data is binarized for one plane. The processing of each color plane is performed independently, and the processing between colors is not related. It is characterized by relating the processing of.

First, if the original image is divided into pixels arranged vertically and horizontally and the pixels are expressed by rows in the vertical direction and columns in the horizontal direction,
The gradation reproduction processing means 4 starts reading from the pixels in the 0th row and 0th column (Step 1 in FIG. 4), and reads the input image data Pij of the pixel (pixel of interest) in the ith row and jth column (Step).
2).

Next, the error with respect to the target pixel diffused and accumulated from the peripheral pixels of the target pixel is read as a correction error from the error memory 10 (Step 3).

Next, the correction error read from the error memory 10 is added to the input image data Pij of the pixel of interest to be corrected in the adder 6 to calculate the input correction data (Step 4). The input correction data is held in the input correction data buffer (Step 5).

The processing from Steps 2 to 5 is performed for the pixels at the same position in the input data of each color. As a result, at this point, the respective input correction data are obtained for the pixels at the same position for the input data of each color. In this description, since the color data is C, M, and Y, the respective correction input data are MIc, MIm, and MIy.

On the other hand, the dot number calculation unit reads the input data value of each color and calculates the number of dots used for reproducing the pixel (Step 6). An example of the dot number calculation method will be described below. As the number of dots, an integer value of a value obtained by dividing the total of input data values by the data value required for 1 dot is used. Input data is 0 to 100%
Expressed as, the input value is C = 80%, M = 50%, Y = 3
In the case of 0%, the total is 160%. Since the data required to form one dot is 100%, 16
0 ÷ 100 = 1.6, and this integer value 1 is the number of dots. FIG. 6 is a graph showing an example of the method of calculating the number of dots. The horizontal axis is the total input data, and the vertical axis is the number of dots. A white circle indicates that the point is excluded. For example, if the total input data is 100, the number of dots is 1.
Becomes

Next, in the binarization control unit, the correction input data corresponding to each color is read, the magnitude relationship of the numerical values is examined and ranked, and the priority of dot generation is set (St.
ep7). For example, if MIc>MIm> MIy, the priority of dot generation is C, M, Y. Further, the dot color to be turned on is determined based on the dot number calculated by the dot number calculation unit. In the above example, the number of dots generated is 1, C is turned on according to the priority, and the other dots M and Y are O.
It is decided not to N.

Next, the binarization control unit for each color converts the input correction data held in the input correction data buffer into two.
The data is binarized based on the decision by the digitization control unit whether to turn it on or not (step 8).

Next, the error calculation unit 8 calculates an error Eij generated by comparing the correction data and the binary data (Step 9).

Next, the error diffusion unit 9 causes the error Eij
Is diffused to surrounding pixels by a predetermined weighting coefficient, the contents of the error memory 10 are updated, and the error is accumulated for each pixel (S
(Step 10).

When the processing of the pixels in the j-th column is completed in this way, j = j + 1, that is, the column is advanced by one column (Step).
11). Then, the processing of the pixels in the column is sequentially advanced, and when the pixel in the last column of the row is reached (Step 12), i = i +
1, that is, the line is advanced by one line, j = 0, that is, the process is started from the first column of the line (Step 13), each time the line is changed, the error memory 10 is shifted by one line, and the last line is completed. Then, all processing is completed (Step 14,
15).

By the way, in the dot number calculation unit, the total number of input data values is divided by the data value required for one dot to obtain the number of dots to be reproduced using an integer value, but in this method, However, since the total value is always underestimated in the direction in which the total value is truncated, there is a tendency that the number of dots of each color generated is reduced, resulting in a lighter print. Therefore, in the present invention, a dot number correction unit that temporarily stores the value rounded down by the dot number calculation unit is provided, and that value is used when processing the next dot. More specifically, in the above embodiment, the input values are C = 80%, M = 50%, Y = 3.
In the case of 0%, the total is 160%, and one dot is generated, but the fractional value of 160% -100% = 60% is truncated. Therefore, the numerical value of 60% is temporarily stored in the dot number correction unit 14. Then, at the time of processing the next pixel, the dot number calculation unit reads the fractional value temporarily stored in the dot number correction unit when reading the input data value of each color and adds it to the input data value.
After that, the number of generated dots is calculated.

FIG. 7 is a table showing each internal data in the case where the dot number correcting unit is used in the case where the processed pixels are moved, when the total value of the input data is constant.
The case where the total input value is 160 and 80 is shown. The vertical direction is the moving processed pixel, and the horizontal direction is the total of input values (constant in this case) in order, the sum of the input values plus a correction value, the number of generated dots, and the correction value (fractional value). In this case, the change cycle was constant at 5 pixels, but when the average of the number of dots generated in one cycle was obtained, it was confirmed that it was the same as the total of the input values, and the brightness of the original image was retained. Was done.

The present invention is not limited to the above embodiment, and various modifications can be carried out as long as the effects of the present invention are exhibited. In this embodiment, the color data is C, M, Y.
However, it is also possible to use R, G, and B, and it is also possible to use four colors such as C, M, Y, and K.

Further, as the error diffusion method, in the above-described embodiment, the error diffusion method in a narrow sense, that is, the method of diffusing the error generated in the target pixel to the unprocessed surrounding pixels with a predetermined weighting coefficient is used. The present invention can be applied to the minimum average error method in which the errors of a plurality of pixels that have already been processed are integrated with a predetermined weighting coefficient to obtain a correction value. In short, in the present invention, the error diffusion method means an error diffusion method in a broad sense including an average error minimum method in addition to the error diffusion method in a narrow sense.

[0040]

According to the color image reproducing method and apparatus of the present invention, smooth gradation reproduction by the error diffusion method can be obtained, and at the same time, the binarization processing for the input data of each color can be performed in association with each other. By arranging the dots so that the dots do not overlap as much as possible, it is possible to reduce the decrease in saturation due to subtractive color mixture, and it is possible to obtain more vivid prints.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of an embodiment of the present invention.

FIG. 2 is a block diagram showing a system that partially includes a gradation reproduction unit.

FIG. 3 is a block diagram showing a configuration of a gradation reproduction processing unit.

FIG. 4 is a flowchart showing a gradation reproduction method of a color gradation image of the present invention.

FIG. 5 is a block diagram showing a basic configuration of an error diffusion method.

FIG. 6 is a graph showing a method of calculating a dot coefficient.

FIG. 7 is a table showing internal data.

[Explanation of symbols]

1 Host computer 2 printer 3 Image data input means 4 gradation reproduction processing means 5 Binary data printing means 6 adder 7 Binarization section 8 Error calculator 9 Error diffusion section 10 Error memory 11 Corrected input value buffer 12-dot number calculator 13 Binarization control unit 14-dot number correction unit 15 Binarization processing unit IN input image data ME correction error MI correction data BI binary data ER error

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Claims (4)

[Claims] 1. The gradation of input data of a color gradation image is set to 2
When converting the values into pseudo values and reproducing the gradation in a pseudo manner, the gradation error between the data before and after the binarization is continuously input as correction data based on a predetermined weighting factor. This is a gradation reproduction method of a color gradation image by an error diffusion method in which the correction input data is binarized by diffusing into the subsequent input image data, and the correction input data is temporarily retained. In addition, it is possible to perform error diffusion processing in parallel with the number of color planes of the color image to be processed, and calculate the number of dots that reproduce the pixel from the input color data. Rank the dot generation order of each color from the calculated number of dots and the value of each color of the input color data,
Further, a gradation reproduction method of a color gradation image is characterized in that for a color dot determined not to generate a dot, a todd is not forcibly generated during binarization. 2. A fractional value for the input color data is temporarily held with respect to the calculated dot number, and correction is performed using the fractional value when calculating the dot number in the subsequent pixel processing. The gradation reproduction method for a color gradation image according to claim 1, 3. An error memory for storing an error of pixels around a pixel of interest, a correction value calculation unit for calculating a correction value using a predetermined weighting coefficient, an input value and the correction value calculation unit. An error is calculated from the difference between the correction input data and the binarization result, the addition unit that obtains the correction input data by adding the correction values calculated in step S4, the binarization unit that binarizes the correction input data. A gradation reproduction device for a color gradation image by an error diffusion processing unit including an error calculation unit, wherein the error diffusion processing unit has a correction input data buffer for temporarily holding correction input data, Further, it has an error diffusion processing unit of a number corresponding to the number of color planes of the color image to be processed, and further, a dot number calculation unit for calculating the number of dots for reproducing the pixel from the input color data, and the dot number calculation unit. A dot number correction unit that corrects the calculated dot number using a fraction, and ranks the dot generation order of each color from the dot number calculated by the dot number calculation unit and the value of each color of the input color data, Further, for a color dot determined not to generate a dot, a binarization control unit that does not forcibly generate a todd in the binarization unit is provided. apparatus. 4. A dot number for temporarily holding a fraction for the input color data with respect to the calculated dot number, and performing correction using the fraction when calculating the dot number in the subsequent pixel processing. The gradation reproduction device for a color gradation image according to claim 3, further comprising a correction unit.