JP2006067510A - Image processor, and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide technologies for facilitating the changing of the number of output gradations or the changing of the number of output gradations for each color component even when a plurality of color components are combined to implement a method of error diffusion, and further, to reduce memory capacity required for performing error diffusion processing to be less than the conventional capacity. <P>SOLUTION: Binary data o0(o1) are found, by combining data g0(g1) resulting from normalizing pixel data I'0(I'1), resulting from adding error data E0(E1) to input pixel data I0(I1) into an integral value within a predetermined range. The difference between data o'0(o'1), resulting from normalizing the binary data o0(o1) into an integral value within a range that the input pixel data (I0, I1) can take, and the pixel data I'0(I'1) are then found as error data E0(E1). <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for error diffusion processing.

  Conventionally, an error diffusion method is known as pseudo-halftone processing for expressing multilevel data in binary ("An Adaptive Algorithm for Spatial Gray Scale" in society for Information Display 1975 Symposium Digest of Technical Papers, 1975, 36). . In this method, the pixel of interest is p, its density is v, and the densities of pixels p0, p1, p2, and p3 located around the pixel of interest p are v0, v1, v2, v3, and threshold values for binarization. Assuming T, first, the binarization error E at the target pixel p is distributed by weight coefficients W0, W1, W2, and W3 empirically obtained for the surrounding pixels p0, p1, p2, and p3, and the average density is obtained in a macro manner. This is a method of equalizing the image density. At this time, if the output binary data obtained by binarizing the pixel of interest is o, the output binary data is obtained as follows.

If v ≧ T, o = 1, E = v−Vmax (1)
If v <T, o = 0, E = v-Vmin
(However, Vmax: maximum density, Vmin: minimum density)
v0 = v0 + E × W0 (2)
v1 = v1 + E × W1 (3)
v2 = v2 + E × W2 (4)
v3 = v3 + E × W3 (5)
(Examples of weighting factors: W0 = 7/16, W1 = 1/16, W2 = 5/16, W3 = 3/16)
Conventionally, when such a method is used to perform pseudo-halftone processing of multiple colors, for example, cyan, magenta, yellow, and black, which are used in color ink jet printers, etc., the above error diffusion method is used independently for each color. Since the processing was performed, when one color was seen, even if the visual characteristics were excellent, good visual characteristics could not always be obtained when two or more colors overlapped.

  In order to improve this drawback, as a conventional technique, there is disclosed a pseudo halftone processing technique capable of obtaining good visual characteristics even when two or more colors overlap by using an error diffusion method by combining two or more colors. (See Patent Documents 1 and 2).

  However, in these methods, when the output corresponding to the input pixel is determined, the output value is determined by a comparator or the like. For example, when the number of output gradations is changed, it is implemented by hardware. If so, the circuit had to be changed significantly, or if implemented by software, the program had to be changed significantly.

  Also, when the number of output gradations of each of the two colors is different, for example, the output gradation of cyan has four values, but magenta has two values, or the number of output colors corresponds to three or more colors. Similarly, even if it was attempted to do so, it could not be dealt with unless the circuit or program was significantly changed.

  As a method for avoiding such a problem, adding means for inputting multi-value image signals of two or more colors and adding error signals from pixels that have already undergone pseudo-gradation processing for each color for each color. Output determining means for determining the pseudo gradation output for each color by referring to the LUT (Look Up Table) with the output from each adding means as input, and the output and color for each color from the output determining means A method of performing processing by providing an error calculation unit for each color that calculates an error in a pixel of interest based on an output from each addition unit has also been considered. According to this configuration, even when the error diffusion method is performed by combining two or more colors, it is possible to easily cope with a plurality of output gradation numbers or adopt different output gradation numbers for each color. Flexible processing can be performed.

  However, in this technique, when the number of colors processed in combination increases to three colors and four colors, the LUT becomes three-dimensional and four-dimensional, so the LUT size increases exponentially. Therefore, the storage capacity of the printing apparatus must be increased accordingly. This is a drawback when designing a printing device. It is also expensive to load a storage device with a large storage capacity.

Looking at the actual ink color composition, it is often composed of a number of colors such as cyan, magenta, black, yellow, light cyan, light magenta, and light black, particularly in gray. In the conventional case, dots of cyan and magenta, cyan and magenta and black, black and light black, etc. are overlapped, resulting in a color dot pattern generated by overlapping two, three, or four color dots. Many were seen. Dot patterns generated by overlapping dots may result in granular noise, or the smoothness of color gradation may be lost. Here, if the above method is used, up to two colors are satisfactory, but the LUT size in the case of three colors or four colors is much larger than in the case of two colors, and the burden on the printing apparatus increases. It costs money.
JP-A-8-279920 Japanese Patent Laid-Open No. 11-10918

  The present invention has been made in view of the above problems. Even when the error diffusion method is performed by combining a plurality of color components, the number of output gradations can be changed or the number of output gradations for each color component can be changed. It is an object of the present invention to provide a technique for facilitating the change of the system.

  Another object of the present invention is to reduce the amount of memory required for performing error diffusion processing as compared with the prior art.

  In order to achieve the object of the present invention, for example, an image processing method of the present invention comprises the following arrangement.

That is, an image processing method,
An input step of inputting a pixel value for each color component of the pixel P;
A division step of dividing the pixel values for each color component input in the input step into a plurality of groups;
An adding step of adding the error value previously calculated for each color component in the group of interest to the pixel value of each color component in the group of interest;
N-value conversion for converting the pixel values of the respective color components in the group of interest into N-values (N ≧ 2) according to the combination of the pixel values of the respective color components after the addition processing in the addition step. A process and an output process for outputting the result of N-value conversion by the N-value conversion process;
A normalization step of normalizing the pixel values of the respective color components that have been N-valued by the N-value conversion step within a range that can be taken by the pixel values of the respective color components in the group of interest at the time of the division;
The difference value between the pixel value of each color component in the target group after addition processing in the addition step and the pixel value of each color component in the target group after normalization processing in the normalization step is calculated. Differential calculation process to
The difference value obtained for each color component in the difference calculation step is added in the addition step to each color component in the group corresponding to the group of interest in the pixel R input next to the pixel P in the input step. Holding process to hold as an error value to be
A repetition step of repeating the addition step, the N-value conversion step, the output step, the normalization step, the difference calculation step, and the holding step for each group divided in the division step. .

  In order to achieve the object of the present invention, for example, an image processing apparatus of the present invention comprises the following arrangement.

That is, an image processing apparatus,
Input means for inputting a pixel value for each color component of the pixel P;
A dividing unit that divides pixel values for each color component input by the input unit into a plurality of groups;
Adding means for adding the error value previously calculated for each color component in the group of interest to the pixel value of each color component in the group of interest;
N-value conversion for converting the pixel values of the respective color components in the group of interest into N-values (N ≧ 2) according to the combination of the pixel values of the respective color components after the addition processing by the addition means Means and output means for outputting the result of the N-value conversion by the N-value conversion means;
Normalizing means for normalizing the pixel values of the respective color components that have been N-valued by the N-value converting means within a range that can be taken by the pixel values of the respective color components in the group of interest at the time of the division;
The difference value between the pixel value of each color component in the group of interest after the addition process by the adding unit and the pixel value of each color component in the group of attention after the normalization process by the normalization unit is calculated. Difference calculation means to
The addition means adds the difference value obtained for each color component by the difference calculation means to each color component in the group corresponding to the group of interest in the pixel R that is input next to the pixel P by the input means. Holding means for holding as an error value to be
A repeating means for repeating the processing by the adding means, the N-value converting means, the output means, the normalizing means, the difference calculating means, and the holding means for each group divided by the dividing means. And

  According to the configuration of the present invention, even when the error diffusion method is performed by combining a plurality of color components, it is possible to easily change the number of output gradations and the number of output gradations for each color component. . In addition, the amount of memory required for performing error diffusion processing can be reduced as compared with the prior art.

  Hereinafter, the present invention will be described in detail according to preferred embodiments with reference to the accompanying drawings.

[First Embodiment]
FIG. 1 is a block diagram showing a basic configuration of an image processing apparatus according to the present embodiment. The image processing apparatus according to the present embodiment inputs 8-bit multi-value pixel data and performs error diffusion processing on the data to convert it into binary data (number of gradations = 2).

  In the figure, I0 and I1 are pixel data of color 0 (for example, cyan) and pixel data of color 1 (for example, magenta), respectively. Since each pixel data is expressed by 8 bits, the pixel value of each color component takes a value of 0 to 255 for one pixel. Input pixel data I0 and I1 are input to adders 1a and 1b, respectively.

  The adder 1a adds the error value indicated by the error data E0 from the pixel that has already undergone the pseudo gradation process to the pixel value indicated by the input pixel data I0 to generate pixel data I′0 (I′0 = I0 + E0). The generated pixel data I′0 is output to the output determination unit 2 and the error calculation unit 3a. On the other hand, the adder 1b adds the error value indicated by the error data E1 from the pixel already subjected to the pseudo gradation processing to the pixel value indicated by the input pixel data I1 (I′1 = I1 + E1), and the pixel data I ′. 1 is generated. The generated pixel data I′1 is output to the output determination unit 2 and the error calculation unit 3b. The error data E0 and E1 will be described later.

  When the first input pixel data I0 and I1 are input to the adders 1a and 1b, there is no error data E0 (E1), so nothing is done and the input pixel data I0 (I1) is input to the input pixel data I. The data is output to the output determination unit 2 and the error calculation unit 3a (3b) as' 0 (I'1), or the above processing is performed with E0 = E1 = 0.

  Here, the output determination unit 2 will be described. FIG. 2 is a block diagram illustrating a basic configuration of the output determination unit 2.

  In the figure, reference numerals 7a and 7b denote LUTs (look-up tables) having the configuration shown in FIG. 10, which respectively receive pixel data I'0 and I'1 and output corresponding values g0 and g1.

  FIG. 10 is a diagram illustrating a configuration example of the LUT (7a, 7b). As shown in the figure, the LUT (7a, 7b) is for normalizing the pixel data (I'0, I'1) to an integer value of 0-8. Therefore, when the pixel data I'0 is input to the LUT 7a, output data g0 corresponding to the pixel data I'0 is output in the table shown in FIG. When the pixel data I'1 is input to the LUT 7b, output data g1 corresponding to the pixel data I'1 is output in the table shown in FIG. The output data g0 and g1 are input to the LUT 4 respectively.

  The LUT 4 outputs binary data o0 corresponding to the data g0 and binary data o1 corresponding to the data g1 by a combination of the value indicated by the input data g0 and the value indicated by the data g1.

  FIG. 3 is a diagram showing the LUT 4. Hereinafter, the LUT 4 will be described with reference to FIG. As shown in FIG. 3 (a), 0 ≦ g0 ≦ 8, 0 ≦ g1 ≦ 8 (within the normalization range by LUTs 7a and 7b), and g0 is one axis (horizontal axis in the figure) and g1 is the other. A distribution of values that can be taken by the binary data o0, o1 determined according to the combination of the values indicated by the respective data of the output data g0, g1 is arranged in the plane having the axis (vertical axis in the figure). . In FIG. 3 (a), black circles, white circles, black triangles, and black squares mean as shown in FIG. 3 (b).

  Therefore, for example, when the value of the data g0 is “5” and the value of the data g1 is “2”, referring to the plane shown in FIG. 3A, it is a black triangle, so the table of FIG. Referring to it, o0 = 1 and o1 = 0. That is, when the value of the data g0 is “5”, the data g0 is binarized to the data o0 of “1”, and when the value of the data g1 is “2”, the data g1 is “0”. The data o1 is binarized.

  In this way, the output determination unit 2 binarizes the pixel data I′0 and I′1 and outputs binary data o0 and o1. The binary data o0 and o1 are output to the outside as an error diffusion processing result for the input pixel data I0 and I1 input to the apparatus.

  Further, when the next pixel data I0 and I1 are input to the adders 1a and 1b, the error calculation units 3a and 3b calculate error data E0 and E1 to be added to the pixel data I0 and I1, respectively. The value data o0 and o1 are input to the error calculators 3a and 3b, respectively.

  FIG. 4 is a block diagram showing a basic configuration of the error calculators 3a and 3b. The binary data o0 (o1) is input to the LUT 5, where it is normalized to an integer value within the range of values indicated by the input pixel data (I0, I1). FIG. 5 is a diagram illustrating a configuration example of the LUT 5.

  The LUT 5 is converted to “0” if the value of the binary data o0 (o1) is 0, and is converted to “255” if the value of the binary data o0 (o1) is 1, as shown in FIG. It is a table. Therefore, the result o′0 (o′1) obtained by normalizing the binary data o0 (o1) to an integer value (0 to 255) within the range indicated by the input pixel data (I0, I1) is output from the LUT5. Is done. The normalized result data o′0 (o′1) is input to the subtracter 6.

  Since the pixel data I′0 (I′1) output from the adder 1a (1b) is input to the subtracter 6 together with the data o′0 (o′1) of the normalization result, Is calculated as follows and obtained as error data.

E0 = I'0-o'0
E1 = I'1-o'1
Therefore, the error calculation unit 3a obtains and holds the error data E0 as described above, and the error calculation unit 3b obtains and holds the error data E1 as described above. Then, the error calculation unit 3a outputs the obtained error data E0 to the adder 1a, and the error calculation unit 3b outputs the obtained error data E1 to the adder 1b. The error data E0 and E1 are for addition when the next input pixel data I0 and I1 are input to the adders 1a and 1b, respectively.

  Thereafter, when the input pixel data I0 and I1 are sequentially input to the image processing apparatus, binary data o0 and o1 corresponding to the input pixel data I0 and I1 are obtained and output, and the next input pixel data is input. Error data E0 and E1 to be added to I0 and I1 are calculated.

  FIG. 17 is a flowchart of the above processing according to the present embodiment. Since the processing in each step is as described above, it is simply performed here.

  First, when the input pixel data I0 (I1) is input to the adder 1a (1b) (step S1701), the adder 1a (1b) indicates the value indicated by the error data E0 (E1) to the value indicated by the input pixel data I0 (I1). Are added to generate pixel data I′0 (I′1), which are output to the output determination unit 2 (step S1702). When the process in this step is performed first, there is no error data E0 (E1). Therefore, the process proceeds to step S1703 without performing the process in this step, or this step is performed with E0 = E1 = 0. The process in is performed.

  The LUT 7a (7b) of the output determination unit 2 generates data g0 (g1) obtained by normalizing the value of the pixel data I′0 (I′1) to an integer value within a predetermined range, and the data g0 and g1 Binary data o0 and o1 are obtained by the combination (step S1703).

  Then, the output determination unit 2 outputs the two binary data o0 and o1 to the outside as error diffusion results for the input pixel data I0 and I1, respectively (step S1704).

  On the other hand, the binary data o0 and o1 are input to the error calculators 3a and 3b, respectively. The error calculation unit 3a (3b) normalizes the input binary data o0 (o1) to an integer value within a range that the input pixel data (I0, I1) can take. 1) is generated (step S1705), and the difference between this and the pixel data I′0 (I′1) from the adder 1a (1b) is obtained as error data E0 (E1) (step S1706).

  Then, the process returns to step S1701, and the subsequent processes are performed until there is no input pixel data input. In other words, the processing for one pixel is completed with the above configuration, so that the above processing is repeated by shifting one pixel at a time in the processing direction to perform processing for one line, and then the same processing is performed by shifting by one raster. By returning, pseudo gradation processing can be performed on the entire image.

  Further, since the LUTs 4 and 5 are configured as shown in FIGS. 3 and 5, for example, two colors are combined to generate an error as disclosed in JP-A-8-279920 and JP-A-11-10918. The same effect as the diffusion method can be obtained.

  In this embodiment, the error data obtained based on the Nth input pixel data is added to the (N + 1) th input pixel data without weighting, but the previously obtained error data is added. A predetermined weighting may be performed and added to the pixel data input this time.

In this embodiment, the case where the input pixel data is 8 bits has been described. However, when the input pixel data is n bits (n = 8 in this embodiment), the numerical value “255” is “2 ^n. " Further, the normalization range in the normalization process is not limited to the above range.

[Second Embodiment]
In the first embodiment, input pixel data is binarized and output, but in the present embodiment, it is binarized and output. That is, the data to be output has three gradations. Hereinafter, the process for ternizing the input pixel data and outputting it will be described. The configuration of the image processing apparatus according to this embodiment is the same as that of the first embodiment except for the points described below.

  First, in the present embodiment, the configurations of the LUTs 7a and 7b are different from those of the first embodiment so that the output is ternary data. FIG. 11 is a diagram illustrating a configuration example of the LUTs 7a and 7b according to the present embodiment. Even if the configurations of the LUTs 7a and 7b are different from those of the first embodiment, the usage method is the same as that of the first embodiment.

  In this embodiment, the configuration of the LUT 4 is different from that of the first embodiment in order to make the output ternary data. FIG. 6 is a diagram showing the LUT 4 according to the present embodiment. As shown in FIG. 6A, 0 ≦ g0 ≦ 6, 0 ≦ g1 ≦ 6 (within the normalization range by LUTs 7a and 7b), and g0 is one axis (horizontal axis in the figure), and g1 is the other. A distribution of values that can be taken by the binary data o0, o1 determined according to the combination of the values indicated by the respective data of the output data g0, g1 is arranged in the plane having the axis (vertical axis in the figure). . In FIG. 6A, the meanings of white circle, black circle, white triangle, black triangle, white square, black square, white star, black star, and double circle are shown in FIG. 6B.

  Therefore, for example, when the value of the data g0 is “1” and the value of the data g1 is “1”, the plane shown in FIG. 6A is a white circle, so refer to the table of FIG. 6B. Then, o0 = 0 and o1 = 0. That is, when the value of the data g0 is “1”, the data g0 is ternarized to the data o0 of “0”, and when the value of the data g1 is “1”, the data g1 is “0”. The data o1 is ternarized.

  In this way, the output determination unit 2 converts the pixel data I′0 and I′1 into three values and outputs ternary data o0 and o1. The ternary data o0 and o1 are output to the outside as error diffusion processing results for the input pixel data I0 and I1 input to this apparatus, and are also input to the error calculators 3a and 3b, respectively.

  The configuration of the LUT 5 is also different from that of the first embodiment in order to make the output ternary data. FIG. 7 is a diagram illustrating a configuration example of the LUT 5 according to the present embodiment. The LUT 5 is converted to “0” if the value of the ternary data o0 (o1) is 0, and is converted to “128” if the value of the ternary data o0 (o1) is 1, as shown in FIG. If the value of the ternary data o0 (o1) is 2, this is a table for conversion to “255”. Therefore, the LUT 5 outputs a result o′0 (o′1) obtained by normalizing the ternary data o0 (o1) to an integer value (0 to 255) within the range of values indicated by the input pixel data (I0, I1). Is done. The normalized result data o′0 (o′1) is input to the subtracter 6.

  That is, as can be seen from the comparison between the first and second embodiments, even if the number of output gradations is changed, only the configuration of the LUT is changed, and the basic device configuration and processing contents are changed. It is not necessary. Accordingly, the flowchart of the basic process when the output gradation is changed is the same as the flowchart shown in FIG. 17 (except for the point that “ternary data output” is set in step S1704).

[Third Embodiment]
In the first and second embodiments, the data o0 and o1 output from the output determination unit 2 are both of the same number of gradations (both gradations in the first embodiment, the second embodiment In this embodiment, the number of gradations is varied. In the following description, a case where o0 is output in three gradations (that is, o0 is ternary data) and o1 is output in two gradations (that is, o1 is binary data) will be described. The configuration of the image processing apparatus according to this embodiment is the same as that of the first embodiment except for the points described below.

  The LUT 7a according to the present embodiment has the configuration shown in FIG. 11 because the output has three gradations. The LUT 7b according to the present embodiment has the configuration shown in FIG. 10 because the output has two gradations. Accordingly, in this embodiment, the data g0 and g1 are normalized within different normalization ranges, and the data g0 is obtained by normalizing the pixel data I′0 to an integer value of 0 to 6. , Data g1 is obtained by normalizing pixel data I′1 to an integer value of 0-8.

  FIG. 8 is a diagram showing the LUT 4 according to the present embodiment. As shown in FIG. 8A, 0 ≦ g0 ≦ 6, 0 ≦ g1 ≦ 8 (within the normalization range by LUTs 7a and 7b), and g0 is one axis (horizontal axis in the figure) and g1 is the other. A distribution of values that can be taken by the binary data o0, o1 determined according to the combination of the values indicated by the respective data of the output data g0, g1 is arranged in the plane having the axis (vertical axis in the figure). . FIG. 8B shows the meanings of white circles, black circles, white triangles, black triangles, white squares, and black squares in FIG. 8A.

  Therefore, for example, when the value of the data g0 is “2” and the value of the data g1 is “5”, referring to the plane shown in FIG. 8A, it is a white triangle, so the table of FIG. Referring to it, o0 = 0 and o1 = 1. That is, when the value of the data g0 is “2”, the data g0 is ternarized to the data o0 of “0”, and when the value of the data g1 is “5”, the data g1 is “1”. The data o1 is binarized.

  In this way, the output determination unit 2 converts the pixel data I′0 into a ternary value, binarizes the pixel data I′1, and outputs a ternary data o0 and a binary data o1. The ternary data o0 and binary data o1 are output to the outside as error diffusion processing results for the input pixel data I0 and I1 input to this apparatus, and are also input to the error calculators 3a and 3b, respectively.

  FIG. 9 is a diagram illustrating a configuration example of the LUT 5 according to the present embodiment. As shown in the figure, the LUT 5 according to the present embodiment includes data of a table 901 and data of a table 902. The configuration of the table 901 is the same as that of the second embodiment, that is, the same as that shown in FIG. 7, and the configuration of the table 902 is the same as that of the first embodiment, that is, the same as that shown in FIG. In this manner, a table corresponding to the number of gradations indicated by the data o0 and o1 is registered in the LUT5.

  Therefore, the table 901 is converted to “0” if the value of the ternary data o0 is 0, and is converted to “128” if the value of the ternary data o0 is 1, as shown in FIG. If the value of 2 is 2, this is a table for conversion to “255”. On the other hand, the table 902 is a table for conversion to “0” if the value of the binary data o1 is 0, and to “255” if the value of the binary data o1 is 1, as shown in FIG. is there.

  Therefore, from the LUT 5, the ternary data o0 is normalized to an integer value (0 to 255) within the range of values indicated by the input pixel data (I0, I1), and the result o′0, the binary data o1 is input pixel data ( The result o′1 normalized to an integer value (0 to 255) within the range of values indicated by I0, I1) is output. The normalized result data o′0 (o′1) is input to the subtracter 6.

  In this way, when the number of gradations of the output data is different from each other, the LUT configuration may be adjusted according to the number of gradations as described above. It is not limited.

  In each of the first to third embodiments, the input pixel data is two (two color components) I0 and I1, but may be three or more. In the embodiment, an adder is provided according to “2”), and a table for normalizing pixel data from each adder (corresponding to LUTs 7a and 7b in the above embodiment) is provided according to the number of inputs. Naturally, the configuration of each LUT is configured in accordance with the number of gradations of the output data. An LUT (corresponding to LUT 4 in the above embodiment) for obtaining an output value is provided in accordance with the combination of outputs from these LUTs. Furthermore, an LUT (corresponding to LUT 5 in the above embodiment) for normalizing each output value to an integer value within a range of values that can be taken by the input pixel data is provided.

[Fourth Embodiment]
In the above embodiment, the LUT 7a (7b) causes the value of the pixel data I′0 (I′1) to be an integer value within a range (0 to 8 in the first embodiment) that is considerably narrower than the range that this value can take. Although normalized to g0 (g1), g0 (g1) after this normalization processing should be a real value instead of an integer value. In the above embodiment, the real value and the integer value The difference was not taken into account. In this embodiment, this difference is taken into consideration.

  FIG. 12 is a diagram illustrating a basic configuration of the output determination unit 2 according to the present embodiment. An LUT 1201a (120b) outputs g0 (g1), dp0 (dp1), and dm0 (dm1) based on the pixel data I′0 (I′1). FIG. 14 is a diagram illustrating a configuration example of the LUT 1201a (1201b). As shown in the figure, the LUT 1201a (1201b) normalizes the value of the pixel data I′0 (I′1) to an integer value within a predetermined range (0 to 8 in the figure) as in the above embodiment. In addition to obtaining g0 (g1), dp0 (dp1) and dm0 (dm1) corresponding to the value of the pixel data I′0 (I′1) are obtained.

  FIG. 13 is a diagram illustrating distances dp0, dp1, dm0, and dm1 with neighboring integer values when the value of the pixel data I′0 (I′1) is actually normalized within a predetermined range.

  In the figure, reference numerals 1351 to 1354 denote the positions of lattice points on the graph in which g0 is the horizontal axis and g1 is the vertical axis, and both g0 and g1 are integer values. Reference numeral 1300 indicates the position of a point on the coordinates (g0 corresponding to the value of the input pixel data I′0, g1 corresponding to the value of I′1) on the graph. As shown in the figure, dp0 and dm0 are values obtained by normalizing the values on the g0 axis of grid points 1351 (1354) and 1352 (1353) adjacent to the point 1300 in the direction of the axis g0 to 0 to 255, respectively. , Dp1 and dm1 indicate lattice points 1351 (1352) adjacent to the point 1300 in the axis g1 direction, respectively, with respect to the value when the value on the g0 axis of the point 1300 is normalized to 0 to 255. , (1353) indicates the distance between the value when the value on the g1 axis of 1354 is normalized to 0 to 255 and the value when the value on the g1 axis of the point 1300 is normalized to 0 to 255. is there. Such dp0, dp1, dm0, dm1 are registered in advance in the table shown in FIG. 14 for each pixel data I′0 (I′1).

  The grid point selection and weight determination unit 9 receives g0, dp0, dm0 from the LUT 1201a and receives g1, dp1, dm1 from the LUT 1201b. First, from these data, three points close to coordinates (g0 corresponding to the value of the input pixel data I′0, g1 corresponding to the value of I′1) on the g0-g1 plane as shown in FIG. Specify the grid points. For example, the identification method will be described with reference to FIG. 13. If dp0> dm0, lattice points 1352 and 1353 are candidates, and if dp1> dm1, lattice points 1353 and 1354 are candidates. Since only the lattice point 1354 is not a candidate at this time, other lattice points, that is, 1351 to 1353 are candidates. If g0, dp0, dm0, g1, dp1, dm1 are used in this way, three grid points close to the coordinates (g0 corresponding to the value of the input pixel data I′0, g1 corresponding to the value of I′1) Can be requested.

  The grid point selection and weight determination unit 9 calculates the weight value w for the three grid points, and various values can be considered for this. For example, the distance between the grid point 1351 and the point 1300 is calculated. The weight for the lattice point 1351, the distance between the lattice point 1352 and the point 1300 is obtained as the weight for the lattice point 1352, and the distance between the lattice point 1353 and the point 1300 is obtained as the weight for the lattice point 1353. The distance can be obtained geometrically by using dp0, dp1, dm0, dm1.

  Since the grid point selection and weight determination unit 9 outputs the values of g0 and g1 of these three grid points to the LUT 4, the oUT and o1 for the respective grid points are output from the LUT 4, so that the interpolation unit 10 The output values for the input pixel data I0 and I1 are obtained using o0 and o1 obtained for these three lattice points and the weight w obtained for each lattice point.

  Here, on the o0-o1 plane, the positions (o0, o1) of the three lattice points and the positions (o0, o1) of one point (output data obtained for the input pixel data) are obtained. In addition, when the weight w for each lattice point has been obtained, the process for calculating the value for this one point is well known, and a description thereof will be omitted.

  Accordingly, output data o0 and o1 for the input pixel data I0 and I1 can be obtained according to the positional relationship with the three lattice points. Even if the number of neighboring grid points is four, the processing to be basically performed is the same.

  The number of input pixel data input in this embodiment is 2, but it may be 3 or more.

[Fifth Embodiment]
FIG. 15 is a diagram illustrating a basic configuration of the image processing apparatus according to the present embodiment. In the present embodiment, an image processing apparatus that handles an image having four or more colors will be described. Actually, the printing apparatus prints using four colors of cyan, magenta, black, and light black, and naturally, the four colors of image data exist in each pixel constituting the image data to be printed.

  As shown in the figure, the configuration of the image processing apparatus according to the present embodiment is obtained by arranging two configurations shown in FIG. 1 in parallel. The output data o0 and o1 for the input pixel data I0 and I1 is output with one configuration, and the output data o2 and o3 for the input pixel data I2 and I3 is output with the other configuration. Each configured device operates independently. In the figure, I0, I1, I2, and I3 are pixel data for color 0 (for example, cyan), pixel data for color 1 (for example, magenta), pixel data for color 2 (for example, black), and color 3 (for example, light black). ) Pixel data.

  With this configuration, when four colors are processed, the number and size of LUTs are doubled compared to the first embodiment. Here, for example, if a four-dimensional LUT is created with a combination of four colors, the number of LUTs does not change compared to the first embodiment, but the size of the LUT is twice that of the first embodiment. Become. This increase in size increases exponentially with the number of colors handled.

  Therefore, if a plurality of colors are handled by a device in which a plurality of devices according to the first embodiment are arranged in parallel, an increase in the size of the LUT can be suppressed. It can be reduced.

[Sixth Embodiment]
In the present embodiment, it is assumed that an image having data of a color portion expressed using seven colors of ink is printed by a printing apparatus configured with seven colors of ink.

  The seven ink colors are divided into three groups of two colors, three colors, and two colors that have a large influence when dots overlap, such as those with close densities and hues. If a device according to the first embodiment is assigned to each of these devices and each device is operated independently, the number of LUTs is three times, the LUT size is about three times, and seven color processing can be performed. When 7 colors are processed as one set, a 7-dimensional LUT is created, and the size of the LUT becomes enormous.

  In this way, even when the number of colors to be handled increases, multi-color processing can be performed with an LUT size that is an integral multiple of the case of two colors by decomposing it into a combination of small colors such as two or three colors. .

[Seventh Embodiment]
In a printing apparatus that includes inks of cyan, magenta, black, and light black, in the region where a * = b * = 0, the process according to the first embodiment is performed for two colors of black and light black. Do. In the region near a * = b * = 0 and excluding a * = b * = 0, two sets of black and light black and two sets of cyan and magenta are used according to the first embodiment. Process. FIG. 16 is a diagram showing processing contents according to the present embodiment. As shown in the figure, the error diffusion process can be performed with less load on the printing apparatus in consideration of the power and color of each color.

[Eighth Embodiment]
Each unit shown in FIG. 1 may be configured with dedicated hardware, or may be implemented with a program.

  In the former case, the LUT is composed of a ROM, and the corresponding table data is stored in this ROM. The image processing apparatus having the configuration shown in FIG. 1 may be incorporated into a printing apparatus or the like.

  On the other hand, in the latter case, each unit shown in FIG. 1 is a program (in accordance with the flowchart shown in FIG. 17) for causing the CPU of the printing apparatus or computer to execute processing to be performed by each unit shown in FIG. The functional configuration of a program for causing the CPU to execute processing may be employed. Such a program may be stored in the ROM in the printing device and executed by the CPU, or may be stored in the hard disk drive of the computer and loaded into the RAM as necessary. The CPU may execute this.

  FIG. 18 is a block diagram showing the basic configuration of such a computer.

  Reference numeral 1801 denotes a CPU which controls the entire computer using programs and data stored in the RAM 1802 and ROM 1803, and performs, for example, processing according to the above embodiments.

  Reference numeral 1802 denotes a RAM which includes an area for temporarily storing programs and data loaded from the external storage device 186 and a work area used by the CPU 1801 for performing various processes.

  Reference numeral 1803 denotes a ROM which stores setting data of the computer and a boot program.

  An operation unit 1804 includes a mouse, a keyboard, and the like, and can input various instructions to the CPU 1801.

  A display unit 1805 includes a CRT, a liquid crystal screen, and the like, and can display a processing result by the CPU 1801 using an image, text, or the like.

  Reference numeral 1806 denotes an external storage device, which is a large-capacity information storage device typified by a hard disk drive device or the like. Are stored in the RAM 1802 under the control of the CPU 1801 and are processed by the CPU 1801. Note that the image data to be processed may be stored here.

  An I / F 1807 is used for data communication with an external device. For example, image data to be processed can be input from the external device.

  Reference numeral 1808 denotes a bus connecting the above-described units.

  The configuration shown in the figure may be, for example, a basic configuration of a general PC (personal computer) or WS (workstation), or a basic configuration of a control system, an operation system, or a display system other than the print processing portion of the printing apparatus. You may make it do.

[Other Embodiments]
The present invention can take an embodiment as, for example, a system, apparatus, method, program, or storage medium. Specifically, the present invention may be applied to a system including a plurality of devices, Moreover, you may apply to the apparatus which consists of one apparatus.

  In the present invention, a software program (in the embodiment, a program corresponding to the flowchart shown in the figure) that realizes the functions of the above-described embodiment is directly or remotely supplied to the system or apparatus, and the computer of the system or apparatus Is also achieved by reading and executing the supplied program code.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention.

  In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, or the like.

  As a recording medium for supplying the program, for example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card ROM, DVD (DVD-ROM, DVD-R) and the like.

  As another program supply method, a client computer browser is used to connect to an Internet homepage, and the computer program of the present invention itself or a compressed file including an automatic installation function is downloaded from the homepage to a recording medium such as a hard disk. Can also be supplied. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and key information for decryption is downloaded from a homepage via the Internet to users who have cleared predetermined conditions. It is also possible to execute the encrypted program by using the key information and install the program on a computer.

  In addition to the functions of the above-described embodiments being realized by the computer executing the read program, the OS running on the computer based on the instruction of the program is a part of the actual processing. Alternatively, the functions of the above-described embodiment can be realized by performing all of them and performing the processing.

  Furthermore, after the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion board or The CPU or the like provided in the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

1 is a block diagram illustrating a basic configuration of an image processing apparatus according to a first embodiment of the present invention. 3 is a block diagram illustrating a basic configuration of an output determination unit 2. FIG. It is the figure shown about LUT4. It is a block diagram which shows the basic composition of the error calculation parts 3a and 3b. It is a figure which shows the structural example of LUT5. It is the figure shown about LUT4 which concerns on the 2nd Embodiment of this invention. It is a figure which shows the structural example of LUT5 which concerns on the 2nd Embodiment of this invention. It is the figure shown about LUT4 which concerns on the 3rd Embodiment of this invention. It is a figure which shows the structural example of LUT5 which concerns on the 3rd Embodiment of this invention. It is a figure which shows the structural example of LUT (7a, 7b). It is a figure which shows the structural example of LUT7a, 7b which concerns on the 2nd Embodiment of this invention. It is a figure which shows the basic composition of the output determination part 2 which concerns on the 4th Embodiment of this invention. FIG. 6 is a diagram illustrating distances dp0, dp1, dm0, and dm1 from neighboring integer values when the value of pixel data I′0 (I′1) is actually normalized within a predetermined range. It is a figure which shows the structural example of LUT1201a (1201b). It is a figure which shows the basic composition of the image processing apparatus which concerns on the 5th Embodiment of this invention. It is a figure which shows the processing content which concerns on the 7th Embodiment of this invention. It is a flowchart of the process which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the basic composition of a computer.

Claims (7)

An image processing method comprising:
An input step of inputting a pixel value for each color component of the pixel P;
A division step of dividing the pixel values for each color component input in the input step into a plurality of groups;
An adding step of adding the error value previously calculated for each color component in the group of interest to the pixel value of each color component in the group of interest;
N-value conversion for converting the pixel values of the respective color components in the group of interest into N-values (N ≧ 2) according to the combination of the pixel values of the respective color components after the addition processing in the addition step. A process and an output process for outputting the result of N-value conversion by the N-value conversion process;
A normalization step of normalizing the pixel values of the respective color components that have been N-valued by the N-value conversion step within a range that can be taken by the pixel values of the respective color components in the group of interest at the time of the division;
The difference value between the pixel value of each color component in the target group after addition processing in the addition step and the pixel value of each color component in the target group after normalization processing in the normalization step is calculated. Difference calculation step to
The difference value obtained for each color component in the difference calculation step is added in the addition step to each color component in the group corresponding to the group of interest in the pixel R input next to the pixel P in the input step. Holding process to hold as an error value to be
A repetition step of repeating the addition step, the N-value conversion step, the output step, the normalization step, the difference calculation step, and the holding step for each group divided in the division step. Image processing method.   In the N-value conversion step, the pixel value for each color component after the addition processing in the addition step is normalized within a predetermined range, and each of the components in the group according to the combination of the normalized pixel values of the color components The image processing method according to claim 1, wherein the pixel value of the color component is converted to an N-value.   The image processing method according to claim 1, wherein the N can be different for each color component.   4. The division step according to claim 1, wherein the pixel value for each color component input in the input step is divided into a color component group having a close density or a color component group having a close hue. The image processing method according to claim 1. An image processing apparatus,
Input means for inputting a pixel value for each color component of the pixel P;
A dividing unit that divides pixel values for each color component input by the input unit into a plurality of groups;
Adding means for adding the error value previously calculated for each color component in the group of interest to the pixel value of each color component in the group of interest;
N-value conversion for converting the pixel values of the respective color components in the group of interest into N-values (N ≧ 2) according to the combination of the pixel values of the respective color components after the addition processing by the addition means Means and output means for outputting the result of the N-value conversion by the N-value conversion means;
Normalizing means for normalizing the pixel values of the respective color components that have been N-valued by the N-value converting means within a range that can be taken by the pixel values of the respective color components in the group of interest at the time of the division;
The difference value between the pixel value of each color component in the group of interest after the addition process by the addition unit and the pixel value of each color component in the group of interest after the normalization process by the normalization unit is calculated. Difference calculation means to
The addition means adds the difference value obtained for each color component by the difference calculation means to each color component in the group corresponding to the group of interest in the pixel R that is input next to the pixel P by the input means. Holding means for holding as an error value to be
A repeating means for repeating the processing by the adding means, the N-value converting means, the output means, the normalizing means, the difference calculating means, and the holding means for each group divided by the dividing means. An image processing apparatus.   A program causing a computer to execute the image processing method according to any one of claims 1 to 4.   A computer-readable storage medium storing the program according to claim 6.

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