JP2001285663A - Data conversion method and image processing apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a data conversion method that applies color conversion employing an LUT properly method to a gamma characteristic of received data to the data almost without increasing a throughput with a minimum memory capacity. SOLUTION: The characteristic of received data is acquired for the LUT used for the color conversion (S503), and an arithmetic operation is conducted in a way that each grating value of the LUT is unchanged and the grid positions are changed so that a conversion value correcting the gamma characteristic of the received data can be obtained at the position of the grid point corresponding to the value of the received data (S504). Then the obtained positions of the grid point are stored in the LUT (S505), and the positions are used for the grid positions of the LUT. The color conversion by the LUT revised in this way is conducted properly corresponding to the gamma characteristic of the received data and this configuration can be realized simply with a small memory capacity.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to a data conversion method and an image processing apparatus, and more particularly to data conversion such as γ conversion and color conversion performed on color image data.

[0002]

2. Description of the Related Art Gamma conversion and color conversion of color image data are performed as image processing when displaying the image on a display or printing with a printer based on the color image data processed by a personal computer, for example.
The color image data handled by such a digital device is expressed, for example, as RGB digital signals.

In general, a color represented by RGB data as it is has characteristics depending on an input device such as a scanner or a display such as a display, and is not an expression method capable of uniquely determining a color by itself. That is, even if all the values of RGB are the same, different colors may be expressed for human vision. For this reason,
Normally, a standard device-independent CIEXYZ system is used, and the RGB data can specify the color represented by being related to this XYZ color space.

[0004] RGB data is expressed by the following equation (1) and
It is related to XYZ by (2).

[0005]

(Equation 1)

[0006] In the above equation, if the RGB characteristics depending on the device of the display or the like as described above is different, the basic and γ in the above formula whereby _{X r Y r Z r X g} Y g Z g
Each value of X _b Y _b Z _b are different.

Of these, the value of γ depends relatively greatly on the device and is affected by RGB characteristics. This γ is called a gamma value and is used because a human perception of a change in lightness is not linear with respect to the signal Y but is more sensitive to a darker one. That is, RGB is used as a digital signal.
When the linear quantization is performed on the signal Y, the gradation in the dark part cannot be expressed sufficiently smoothly. Therefore, when γ is set to a value larger than 1, the change in RGB matches the change perceived by humans. Like that. Note that the gamma value changes according to the characteristics of the signal RGB as described above, and the range of the change is approximately 1.4 to 2.2.

As described above, since the gamma value has a width, a situation may occur in which the RGB gamma value assumed in the color conversion process is different from the RGB gamma value of the input image data. If color conversion is performed without any correction despite such gamma value mismatch, a normal result cannot be obtained.

For example, if the gamma values do not match,
The resulting image may be darker or brighter
Or By the way, the parameters of the transformation matrix
X _rY_rZ_rAbout image data and color conversion processing
Colors are mainly used when what is assumed is different from each other
The hue and saturation may change, but the hue and saturation may shift slightly.
Is more about image evaluation than being about inadequate brightness.
The effect of blurring is small. That is, color conversion for an RGB image
In processing, it is more important to correct for differences in gamma values.
You.

Conventionally, the following three methods are known as methods of color conversion processing including gamma value correction.

In the first method, a dedicated color conversion is prepared for each of a plurality of input characteristics, for example, scanners having gamma values of 1.8 and 2.2, respectively.

A second method corrects for differences in gamma values.
A plurality of one-dimensional tables (hereinafter referred to as gamma conversion tables) are prepared, and these are switched and used according to the gamma value of input image data, and color conversion is performed on image data corrected thereby. For example, if the standard color conversion set in the table assumes that the gamma value is 1.8, the gamma value is 1.4 or 2.
When image data having the characteristic of 2 is input, 1.8 is input.
Performs conversion equivalent to /1.4 or 1.8 / 2.2 gamma correction
Prepare a one-dimensional table. After correcting the values of the input image data RGB using the one-dimensional table, color conversion is performed.

In a third method, a plurality of sets of input values of RGB are subjected to the above-mentioned γ correction, and a plurality of sets obtained by performing the above-described γ correction are used as input to obtain an output of color conversion. The obtained value is used as the value of the grid point of the LUT and L
A UT is constructed, and color conversion is performed on RGB input values using the LUT.

[0014]

However, the first method uses a look-up table (hereinafter, LUT) for color conversion.
There is a point that it is difficult to use when the conversion is based on This is because in color conversion of a color image, at least the input is three-dimensional or more, so the LUT is also a three-dimensional LUT, and since the data amount is extremely large, an extremely large storage area is required to store a plurality of such data.

In the second method, the conversion causes gradation collapse or jump, which tends to hinder smooth gradation reproduction. For example, RGB with a gamma value of 1.8
Each 8-bit human data is converted into 8 RGB data each having a gamma value of 2.2.
When converting to bits, inputs 0, 1, 2, 3, 4, ..., 248, 249, 25
0, 251, 252, 253, 254, 255 output 0, 3, 5, 7, 9, ..., 249, 250, 25
Conversion such as 1, 252, 253, 253, 254, 255 is performed for each of RGB, and the gradation jumps around 0 (in the actually output image, the change in the gradation value indicated by the input data indicates that A large change in gradation occurs), and the gradation collapse occurs near 255 (the gradation does not change as much as the change in the gradation value indicated by the input data in an actually output image). Conversely, an RG having a gamma value of 2.2
When converting 8 bits of B input data into 8 bits of RGB having a gamma value of 1.8, inputs 0, 1, 2, 3, 4, ..., 248, 249, 25
0, 251, 252, 253, 254, 255 output 0, 0, 1, 1, 2, ..., 246, 248, 24
Conversions such as 9, 250, 251, 253, 254, and 255 are performed for each of RGB, so that gradation collapse occurs near 0 and gradation jump occurs near 255. It should be noted that such a gradation collapse or jump can be caused by the number of input and output bits in any conversion table except when the input and output are exactly the same, not only when performing gamma conversion. It always occurs if they are the same.

In order to eliminate gradation collapse and jump, for example, it is necessary to increase the number of bits on the output side, but in that case, the size of the gamma conversion table becomes large. In addition, since the subsequent conversion also needs to correspond to an input having a large number of bits, the amount of memory required for processing increases or the processing amount increases, resulting in a reduction in speed.

The second method also has a problem that extra processing time is required because gamma correction processing is performed separately from the original color conversion processing.

The third method can be considered as a simplified method of combining a one-dimensional gamma conversion table and a three-dimensional color conversion table. This method minimizes the occurrence of gradation collapse, eliminates the need to perform gamma correction processing separately from the color conversion processing, and can realize high-speed processing. This is the most preferred method. Further, even when the grid position is fixed in the conversion processing, it can be used.

However, in the third method, when color conversion using an LUT is used, another LUT is created while performing conversion using the LUT, so that a large amount of memory area is temporarily required. For example, if the LUT to be created has a grid number of 17 and an output of 3 bytes, 17 × 17
× 17 × 3 = 14739 bytes ≒ 14.4 Kbytes of extra memory area is required.

Further, the conversion output from the original LUT is CM
In the case of four or more dimensions such as YK, there is a high possibility that an output that does not appear in the conversion using the original LUT will occur due to the reconstruction of the LUT.

In addition, this method is disadvantageous in terms of processing time because processing for creating a new LUT is performed.

The present invention has been made to solve these problems. It is an object of the present invention to minimize the amount of memory required for characteristics such as gamma characteristics in input data in data conversion using an LUT. It is still another object of the present invention to provide a data conversion method and an image processing apparatus capable of performing data conversion with little increase in processing amount and with minimal loss of gradation information.

[0023]

According to the present invention, there is provided:
A data conversion method for converting input data by a look-up table and outputting data, wherein the look-up table does not change the value of the grid point in accordance with a predetermined characteristic relating to data processing of the input data. A step of performing a process of changing a position of a grid point corresponding to the value of the grid point, and performing data conversion using the lookup table on which the process is performed.

Further, the processing for changing the position of the lattice point includes reading lattice position data corresponding to the input data from a plurality of lattice position data stored in a predetermined memory in advance, and converting the lattice position data. In another aspect, the image processing apparatus performs data conversion in which input data is converted by a lookup table and data is output. According to a predetermined characteristic concerning data processing of input data in the lookup table,
Changing means for performing a process of changing the position of a grid point corresponding to the value of the grid point without changing the value of the grid point, and performing data conversion using a lookup table subjected to the changing process by the means. Conversion means for performing the conversion.

According to the above arrangement, when performing a data conversion according to the predetermined characteristic relating to the data processing of the input data using the look-up table, the value of the grid point is determined according to the predetermined characteristic. Performs processing to change the position of the grid point corresponding to the value of the grid point without changing
Since the data conversion is performed using the look-up table subjected to this processing, the conversion of the look-up table can be determined by the relationship between the position of the grid point corresponding to the input data and the value of the grid point output thereby. The characteristics can be changed only by the process of changing the positions of the lattice points, and data conversion can be performed based on the changed characteristics.

[0026]

Embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is a block diagram showing the configuration of an image processing system according to one embodiment of the present invention.

In FIG. 1, a host 100 as an image processing apparatus is realized, for example, as a personal computer, and includes a CPU 10, a memory 11 such as a ROM and a RAM, an interface for communication with a printer 200, and the like. , An external storage device 13, a display device 15 such as a CRT, and an input device 12 such as a keyboard. The CPU 10 executes various processes in accordance with the programs stored in the memory 11. In particular, the CPU 10 performs image processing associated with printing described later with reference to FIG. 2 and the LUT according to the present embodiment described later with reference to FIG. 5. Is executed. Specifically, these processes can be performed as processes of the printer driver. Programs for these processes are stored in the external storage device 13 or can be supplied from other external devices not shown in the figure. The host 100 is connected to a printer 200 as a printing device via an interface, and can transmit print data subjected to image processing to the printer 200 to perform printing.

The above-described printer 200 is of an ink jet type which performs printing by discharging ink onto a printing paper to be conveyed, and is provided with a recording head for discharging ink. The recording head according to the present embodiment is of a so-called bubble jet (registered trademark) system in which bubbles are generated in ink by using thermal energy generated by the electrothermal conversion element, and the ink is ejected by the pressure of the bubbles.
In the application of the present invention, it goes without saying that the printing method of the printer is not limited to the above. For example, it is clear that the present invention can be applied to a case where an electrophotographic printer is used.

In the present embodiment, the host 100 fulfills the function of the image processing apparatus. The printer has the function of image processing described below. You can do it. Alternatively, the functions of the image processing apparatus may be divided between the host and the printer.

Next, image processing when the host 100 generates print data used by the above-described printer will be described.

FIG. 2 is a block diagram showing the configuration of this image processing. Red (R), green (G),
An image in which 8-bit image data of each color of blue (B) (256 gradations each) is finally output as bit image data of 1 bit for each color of cyan (C), magenta (M), yellow (Y), and black (K). The processing is shown.

As shown in FIG. 2, luminance data of 8 bits for each of R, G, and B is first converted into R ', G', and B's by a first color conversion process using a three-dimensional lookup table (LUT) 201. 'Converted to 8-bit data for each color. The color conversion processing from the R, G, B data to the R ', G', B 'data is performed by combining the input gamma correction and the color conversion processing shown in the equations (1) and (2). However, in the present embodiment, the processing for changing the lattice point position described later with reference to FIG. 5 is suitable for coping with various gamma characteristics of R, G, and B data input with a simple configuration. It performs a color conversion process.

The first color conversion process is a process for correcting the difference between the color space of the input image represented by the luminance data and the color space reproducible by the printer 200. As described above, the R, G, B luminance data Performs a color space conversion process of converting the color space of the input image represented by the device-independent color space into a device-independent XYZ color space, and a process of converting the device-independent color space into a color space that depends on the printer 200. However, in FIG. 2, the results of these conversion processes are represented as signals R'G'B '. In addition, this processing is performed by the three-dimensional L
It is performed using a UT, but it is the same as a well-known one that does not have grid points for all combinations of inputs and uses interpolation processing together.

However, since the lattice point positions are changed and the lattice point intervals are not equal, the interpolation processing according to this is
For example, JP-A-8-237497 and JP-A-2000-237497
This can be performed using the configuration described in Japanese Patent No. 22973. This means that when the grid point intervals are not equal, the respective intervals are held in advance as a table, and the RGB values input to the LUT, that is, the intervals are read from the table according to the grid point positions and used for interpolation calculation. It is.

The R ', G',
B ′ 8-bit data for each color is output to the next three-dimensional LUT 202
Are converted into 8-bit data for each color of C, M, Y, and K. The second color conversion processing is a processing of performing color conversion from input RGB data represented by a luminance signal to output CMYK data representing a density signal, masking, under color removal, black generation, and the like. This is the process.

Note that the LUT 202 is also
Similarly to 201, table data is not prepared corresponding to all combinations of 8-bit data for each color due to the limitation of the memory capacity.
For example, only data for points at a predetermined interval among points in a three-dimensional space are prepared, and therefore, conversion of 8-bit data of points other than the points at the predetermined interval is performed using interpolation processing.

The 8-bit data of each color of C, M, Y, and K obtained by the second color conversion processing by the LUT 202 is subjected to output γ correction by the one-dimensional LUT 203 of each color. This is a process performed because the number of dots recorded per unit area of the print medium and the output characteristics such as the reflection density obtained by measuring the dots do not usually have a linear relationship. Therefore, by performing the output gamma correction, it is possible to guarantee a linear relationship between the input gradation level of each of the 8 bits of C, M, Y, and K and the density level of the image recorded thereby. In addition, the second color conversion processing and the output gamma processing are also combined processing similar to the first color conversion processing, and by applying the present invention, changing the grid point position to change the appropriate It is clear from the following description that the color conversion can be performed.

After the above output gamma correction, binarization processing 2
04 is performed. Since the printer 200 of this embodiment is a binary printing device, the 8-bit data of each color of C, M, Y, and K obtained as described above is quantized into 1-bit data of each of C, M, Y, and K colors. Be transformed into

In the present embodiment, an error diffusion method is used as a binarization method because the binarization is realized by expressing the gradation change smoothly by the binary recording printer 200. Since the quantization method using this error diffusion method is a known technique itself, its description is omitted here.

Hereinafter, with respect to the three-dimensional LUT which performs the first color conversion processing 201, the lattice point positions are changed according to the gamma characteristics of the input RGB, and thus the gamma correction and the predetermined color conversion are combined. A process according to an embodiment of the present invention will be described in which color conversion by an LUT corresponds to characteristics of input data and does not impair gradation information.

The first color conversion processing 201 is a conversion processing for outputting RGB, and when this is realized by an LUT, each grid value becomes an RGB value such as (83, 253, 19). Assuming that each of the RGB values is 8 bits and the number of grid points on each axis is 17, the total data amount of the grid values is 17 ×
17 × 17 × 3 = 14739 bytes, and this set of lattice values (hereinafter, lattice value sequence) is the actual state of the LUT. In the case of a three-dimensional LUT, a grid point can be specified by three integers of 1 to the number of grid points, such as (n0, n1, n2). Further, the RGB values of the grid value can be associated with XYZ by colorimetry or conversion by an expression such as Expressions (1) and (2).

In response to this, the LUT is a set of lattice values, and its output is determined by the lattice value. However, what conversion is performed by the LUT cannot be determined unless the lattice position of each axis is determined. . That is, the output obtained for the input can be greatly changed by changing the grid position. In most cases, the LUT used for color conversion has the same lattice position for each of the RGB axes. This is because by setting the grid points on the achromatic color axis of R = G = B, it is possible to minimize the influence of the interpolation processing on the achromatic color and realize good achromatic color reproduction.

Therefore, when conversion corresponding to a plurality of gamma values is realized by one LUT, an achromatic axis, that is, a grid point
The lattice position is determined so that Y in (i, i, i) achieves the desired characteristics. In other words, one-dimensional input
(i) It is sufficient to consider the -Y characteristic, and the lattice position is RGB.
It is the same for each axis.

Of course, it is also possible to determine the grid position individually for each of the R, G and B axes. For example, the grid position of R is determined so that Y in the axis of G = B = 0 has desired characteristics, and the grid position of G is Y in the axis of R = B = 255.
And the lattice position of B is Y at the axis of R = 23 and G = 82.
Can be determined so as to achieve the desired results in the same manner as described below.

Hereinafter, a method of changing the grid point position will be specifically described. As described above, the number of grid points for each of RGB is 17, and Y realized by the value of each grid point where R = G = B is the first grid 0.06000 the second grid 0.07679 the third Grid 0.09645 fourth grid 0.11920 fifth grid 0.14529 sixth grid 0.17491 seventh grid 0.20832 eighth grid 0.24573 ninth grid 0.28737 tenth Lattice 0.33347 Eleventh lattice 0.38425 Twelve lattice 0.43994 Thirteenth lattice 0.50077 Fourteenth lattice 0.56697 Fifteenth lattice 0.63875 Sixteenth lattice 0.71635 Seventeenth lattice 0.80000.

In an image processing system having such an input-Y characteristic, gamma values are 1.4, 1.
When there is an input having a characteristic of 8 or 2.2, it is considered to realize an input-Y conversion as shown in FIGS. There are several methods for obtaining a grid position that realizes the characteristics as shown in FIG. 3. Here, a case where the simplest grid is placed on the curve shown in FIG. 3 will be described as an example.

First, it is obvious that the first grid position corresponds to 0 which is the minimum value of the input in each conversion shown in FIG. In order to determine the second grid position, since Y of the second grid is 0.07679, FIG.
For each of the curves shown in (a), (b) and (c), Y =
Find the intersection with 0.07679. Γ shown in FIG.
In the curve of 1.4, the lattice point position (input value) is 16, and FIG.
Γ shown in FIG. 18 is 24 at 1.8, and γ shown in FIG.
Then it becomes 36. Therefore, the second lattice positions are 16, 24, and 36 for each gamma characteristic. Similarly, the third to sixteenth lattice positions are obtained.
It is obvious that the seventeenth grid position is 255, which is the maximum plant of the input.

The respective grid position strings thus obtained are shown below.

Γ: 0 16 29 42 55 67 80 80 92 10 for the input-Y curve of 1.4
5 118 132 147 162 181 203 203 227 255 γ: For input-Y curve of 1.8, 0 24 43 59 74 88 88 102 114
126 139 152 166 181 196 2
14 233 255 For input-Y curve of γ: 2.2, 0 36 58 76 94 107 120 120 133
145 157 169 180 193 206 220 235 2
55 Input realized when the grid position is set as described above-Y
Are shown in FIGS. 4A to 4C, respectively.

As shown in FIGS. 4 (a) to 4 (c), according to this embodiment, {one LU can be obtained by adding only a relatively small amount of information, such as a row of grid positions corresponding to each gamma characteristic}.
Thus, various conversion characteristics can be realized.

In the above description, a case has been described in which three types of conversion characteristics are realized for the gamma characteristic, but it is clear that the number of types of the conversion characteristics is not limited.

The grid position sequence obtained as described above is shown in FIG.
As will be described later, when performing image processing at the time of printing, a grid position sequence corresponding to the gamma characteristic of the input data is read out, and the LU for the first color conversion processing is read.
と し て is used as the position of the lattice point.

FIG. 5 is a flowchart showing a process related to the above-described change of the lattice point.

This process is a process that is performed in advance in accordance with, for example, the characteristics of the input data that is expected by the image processing system. When this processing is started, first, in step S501,
, An initial value 0 is set for I, which is a parameter indicating which of the RGB processing is to be performed. By setting this 0, first, the following lattice position changing process is performed on R. In step S502, a parameter J indicating which of the gamma values is to be processed is initialized. In the present embodiment, the gamma value is 1.4, 1.8, or 2.2 as described above, and the following processing is performed for all of them. This gamma value is set according to the characteristics of the input data as described above.

Next, in step S503, a gamma value is obtained. Specifically, a gamma value corresponding to the value indicated by the parameter J is obtained. Then, in step S504, a process of calculating a grid point position to be changed as described above in accordance with the acquired gamma value, obtaining this as a grid position sequence, and storing it in a predetermined table of the memory 11 is performed.

Next, in step S505, the grid position sequence obtained as described above is stored in a predetermined area of the memory 11 in a manner described later.

Further, in step S506, it is determined whether or not the value of the parameter I is 2, and if not, the value is incremented (step S50).
7) The above-described processing is sequentially repeated for G, B, and the like. Similarly, in step S508, it is determined whether or not the value of the parameter J is 2, and accordingly, the above processing is performed for all of γ of 1.4, 1.8, and 2.2, and this processing is performed. finish.

The calculation of the lattice position described above may be performed by the host 100 and the result may be stored in the memory 11 or the external storage device 13, or may be calculated by another data processing device (not shown). Only the obtained lattice position sequence may be stored in the external storage device 13 or the like, and the host 100 may use the lattice position sequence when performing image processing.

Next, a description will be given of a storage form of the obtained lattice position sequence, which is the processing of step S505. This storage can be performed in several forms, and this embodiment can adopt any form.

The first method, as shown in FIG. 6, shows a form in which a grid position sequence is stored for each of the three-dimensional input RGB corresponding to one of the gamma values, and an LUT corresponding to the grid position sequence is stored. 5 shows a form in which the information is stored together with the lattice value sequence used in the step (a). In this case, since the length of all the grid position rows is always the same as the number of grids of the grid value and is constant, it is sufficient to simply list the grid position rows. Although this method is the simplest and is sufficient in many cases, this method does not allow a plurality of lattice value sequences to share a lattice position sequence.

As shown in FIGS. 7 (a) and 7 (b), the second method is to enumerate and store, for example, N grid positions of the same number of grids corresponding to the same gamma value. As a position sequence group, an identifier indicating the lattice position sequence is stored together with the lattice value sequence. It is sufficient for the grid position sequence identifier to include an identifier for specifying the grid position sequence group and an identifier for specifying the grid position sequence in the grid position sequence group. Further, by storing the grid position rows having the same number of grids in one grid position row group, the grid number of the grid value row can be used as an identifier of the grid position row group. Is unnecessary to be included, and the size of the lattice position column identifier can be reduced. Than this,
The same grid position row can be used between a plurality of grid value rows, and the area of the LUT can be reduced.

The third method is to store a grid position sequence having an irregular number of grids in one grid position sequence group.

As shown in FIGS. 8 (a) and 8 (b), an area necessary for storing the longest of the stored grid position strings is allocated to all the grid position strings. In this way, a grid position sequence having a different number of grids can be stored in one grid position sequence group, but in this method, the longest grid position sequence is considerably longer than the length of most other grid position sequences. If it is long, many unused areas are generated, and the efficiency is reduced.

The fourth method solves the problem of the third method, and stores a grid position sequence having an inconsistent number of grids in one grid position sequence group.

As shown in FIGS. 9A and 9B, a table including an offset address from the head of the grid position column group to each grid position column is prepared. To obtain the grid position sequence, first, an offset address is obtained from the offset address table based on the grid position information identifier. next,
By adding the offset address to the head address of the lattice position sequence group, a desired lattice position sequence can be obtained. Since grid position rows with different numbers of grids can be stored in one grid position row group, there is no need to prepare multiple grid position row groups, and information for identifying grid position row groups is stored in grid position information identifiers and offset addresses. do not have to. According to this method, it is possible to successively store the lattice position strings having different lengths, so that the storage area can be efficiently utilized.

The fifth method is to store a general-purpose link to a lattice position sequence together with a lattice value sequence.

As shown in FIG. 10, a URI
By storing an information identifier that does not depend on a specific recording medium together with the lattice value sequence, the storage location and method of the lattice position sequence can be set freely.

The grid position sequence and the grid value sequence stored as described above are read out according to the characteristics of input data such as a gamma value at the time of image processing for printing, and are subjected to the first color conversion processing 201 described above. These are used as grid positions and grid values of the LUT, respectively. In this case, the actual input / output conversion processing in the configuration of the LUT shown in FIG.
One grid point is specified from each of the N (3) grid position rows according to the dimension input, and one grid value (conversion value) is specified from the grid value row according to the combination of the grid points. And output, whereby color conversion is performed.

Note that the processing shown in FIG. 5 can be performed each time image processing for printing is performed, and a plurality of grid position data can be dealt with without being stored in advance as shown in FIGS. .

The embodiment of the present invention has been described above. However, the present invention is not limited to this embodiment, and various modifications, improvements or modifications may be made without departing from the scope of the invention. be able to. For example, in the above description, the case where the number of pieces of information related to the change of the grid position is fixed to 3 is exemplified. This can be dealt with by providing.

Even when the input of the LUT is multi-dimensional, if the lattice positions of all dimensions are the same, the same implementation as the above-described method can be performed. That is, in general, a three-dimensional LUT is used in color conversion. However, since the three dimensions usually have the same lattice position, when the γ characteristics of each dimension are the same, the processing described with reference to FIG. What is necessary is just to perform about a dimension. That is, the process may be executed for one value of the parameter I.

Further, when the input of the LUT is multi-dimensional, it is possible to easily provide each grid with a different grid position by preparing a grid position sequence by the number of dimensions. It is apparent from the above description that the present invention can be implemented regardless of the number of output dimensions of the LUT. Further, the present invention is of course effective not only in the case where the input is RGB, but also in a conversion process in which another color space such as gray, CMY or CMYK is input.

<Other Embodiments> The present invention, as described above,
The present invention may be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, and the like) or may be applied to an apparatus including one device (for example, a copying machine and a facsimile machine).

Further, the functions of the embodiment shown in FIG. 5 are implemented in an apparatus connected to the various devices or a computer in the system so as to operate various devices so as to realize the functions of the above-described embodiment. Computer software (CPU or MPU) for the system or device
The present invention also includes those implemented by operating the various devices in accordance with the stored program.

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

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

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

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

[0080]

As is apparent from the above description, according to the present invention, when a look-up table is used and data conversion is performed in accordance with predetermined characteristics relating to data processing of the input data, the predetermined characteristics are obtained. In accordance with, the process of changing the position of the grid point corresponding to the value of the grid point without changing the value of the grid point is performed, and data conversion is performed using the lookup table subjected to this process. The conversion characteristics of the look-up table, which can be determined by the relationship between the position of the grid point corresponding to the input data and the value of the grid point output thereby, can be changed only by the process of changing the position of the grid point, Data conversion can be performed by the changed characteristics.

As a result, in the data conversion such as the color conversion using the LUT, the data conversion appropriately corresponding to the characteristics of the input data can be performed with the minimum memory amount and without substantially increasing the processing amount. It can be realized without losing information.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing system according to an embodiment of the present invention.

FIG. 2 is a block diagram illustrating a configuration of image processing for printing in the image processing system.

FIGS. 3A, 3B, and 3C are diagrams illustrating an example of an input-Y characteristic to be realized for each gamma characteristic in the image processing. FIG.

FIGS. 4A, 4B, and 4C are diagrams illustrating input-Y characteristics realized as a result of changing a grid position. FIGS.

FIG. 5 is a flowchart showing a process for changing the lattice position.

FIG. 6 is a diagram illustrating a first method of storing a grid position obtained by changing a grid position in the above processing.

FIGS. 7A and 7B are diagrams for explaining a second method of storing a grid position obtained by changing a grid position in the above processing.

FIGS. 8A and 8B are diagrams illustrating a third method of storing a grid position obtained by changing a grid position in the above processing.

FIGS. 9A, 9B and 9C are diagrams for explaining a fourth method for storing the grid position obtained by changing the grid position in the above processing.

FIG. 10 is a diagram illustrating a fifth method of storing a grid position obtained by changing a grid position in the above processing.

[Explanation of symbols]

 Reference Signs List 10 CPU 11 Memory 12 Input device 13 External storage device 14 Interface 15 Display device 100 Host 200 Printer 201 First image processing 202 Second image processing 203 Output γ processing 204 Binarization processing

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Claims (14)

[Claims] 1. A data conversion method for converting input data using a look-up table and outputting data, wherein the value of the grid point is determined in the look-up table according to a predetermined characteristic relating to data processing of the input data. Performing a process of changing the position of the grid point corresponding to the value of the grid point without changing the value of the grid point, and performing a data conversion using the lookup table subjected to the process. Conversion method. 2. The process of changing the position of a grid point includes reading grid position data corresponding to the input data from a plurality of grid position data stored in a predetermined memory in advance, and looking up the grid position data. 2. The data conversion method according to claim 1, wherein the processing is a grid position of an up table. 3. The look-up table is an N-dimensional look-up table, and the processing of changing the position of the grid point changes the position of the grid point according to the predetermined characteristic for each of the N-dimensional inputs. 3. The data conversion method according to claim 1, wherein the data conversion is performed. 4. The N-dimensional lookup table according to claim 1, wherein
4. The data conversion method according to claim 3, wherein the data conversion method is a three-dimensional table for a three-dimensional GB input. 5. The data conversion method according to claim 4, wherein the positions of the grid points are the same for the three-dimensional input. 6. The method according to claim 4, wherein the predetermined characteristic is a γ characteristic in processing of image data, and the data conversion includes a conversion for correcting a gamma characteristic of the input data. Data conversion method described. 7. An image processing apparatus for performing data conversion of converting input data by a look-up table and outputting data, wherein the look-up table is adapted to perform predetermined data processing on input data. Means for performing a process of changing the position of a grid point corresponding to the value of the grid point without changing the value of the grid point; and data conversion using a look-up table that has been subjected to the change process by the means. An image processing apparatus comprising: a conversion unit that performs the following. 8. The change unit reads grid position data corresponding to the input data from a plurality of grid position data stored in a predetermined memory in advance, and reads the grid position data with grid position data of a lookup table. The image processing apparatus according to claim 7, wherein the processing is performed by performing the processing. 9. The method according to claim 9, wherein the lookup table is an N-dimensional lookup table, and the changing means performs processing for changing the position of the grid point independently of the N-dimensional input according to the predetermined characteristic. The image processing device according to claim 7 or 8, wherein 10. The N-dimensional look-up table,
The image processing apparatus according to claim 9, wherein the image processing apparatus is a three-dimensional table for three-dimensional input of RGB. 11. The image processing apparatus according to claim 10, wherein the positions of the grid points are the same for the three-dimensional input. 12. The method according to claim 10, wherein the predetermined characteristic is a γ characteristic in image data processing, and the data conversion includes a conversion for correcting a gamma characteristic of the input data. The image processing apparatus according to any one of the preceding claims. 13. A storage medium storing a program readable by an information processing apparatus, wherein the program is a data conversion process of converting input data using a look-up table and outputting data. In the table, a process of changing the position of the grid point corresponding to the value of the grid point without changing the value of the grid point is performed according to a predetermined characteristic related to the data processing of the input data. A storage medium including a process having a step of performing data conversion using a look-up table. 14. The process of changing the position of a grid point,
A process for reading grid position data corresponding to the input data from a plurality of grid position data stored in a predetermined memory in advance, and using the grid position data as a grid position in a lookup table. Item 14. The storage medium according to Item 13.