JP2002209114A - Method for storing color conversion table and image processing apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve compressibility in the data compression of a color conversion table to be used for image processing to store it in a storage medium. SOLUTION: Concerning the respective axial directions of the inputting space of the color conversion table, the changing rate of table data is investigated and the table data is rearranged in the increasing order of the changing rate of an axis (S101). With this processing, the rearranged table data is given difference along the axis or in a straight line parallel with the axis in the increasing order of the changing rate of the axis (S105, S109 and S112) and data compression is given to the data given difference (S115). As the result of this, the run length of a neighboring value is extended and correlation between data can be improved more by giving difference to it, thereby compressibility in data compression is improved.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for storing a color conversion table and an image processing apparatus. The present invention relates to an image processing apparatus for performing a method of storing a color conversion table, and performing image processing using a stored color conversion table.

[0002]

2. Description of the Related Art In image processing for generating image data used in a color image output device such as a color printer or a color copying machine, color conversion is performed as luminance-density conversion, masking processing, or processing integrating these conversion processing. Is being done. In this color conversion, a table is used, and an interpolation method is generally used together from the viewpoint of the data capacity of the table. In this interpolation method, instead of having an enormous amount of table data describing all input / output relations in the conversion, a grid-like space consisting of predetermined input data obtained by thinning out the input space is used, and the output at the grid point is output. A table in which only values are stored as data (hereinafter, also referred to as table data) (hereinafter, also referred to as a color conversion table) is used, and an output value for an arbitrary input is obtained by interpolation of the table data.

For example, R (red), G (green), B
(Blue) CMYK from RGB space consisting of data of each color
When considering conversion to space, if the conversion tables for C (cyan), M (magenta), Y (yellow), and K (black) are Tc, Tm, Ty, and Tk, C, M, Y,
Each output value of K is generally C = F (Tc1 (R, G, B), Tc2 (R, G, B),.
, Tcn (R, G, B), R, G, B) M = F (Tm1 (R, G, B), Tm2 (R, G, B),...
, Tmn (R, G, B), R, G, B) Y = F (Ty1 (R, G, B), Ty2 (R, G, B),...
, Tyn (R, G, B), R, G, B) K = F (Tk1 (R, G, B), Tk2 (R, G, B),...
, Tkn (R, G, B), R, G, B).

Here, Tpn (R, G, B) (p = C,
M, Y, and K) are plural (n) from the input (RGB) coordinates.
F (.) Is a function that interpolates the output values C, M, Y, and K from those values and the input coordinates (R, G, B). is there. They are,
It is determined according to the interpolation method used, and various methods have been proposed.

[0005] In the case of performing such a color conversion process using an interpolation operation together with a table with high accuracy, it is effective to reduce the thinning rate of the input space in the color conversion table and increase the number of grid points. This is one of the methods. However, in that case, the amount of data in the table increases, which results in pressure on resources such as memory.

On the other hand, data compression is known as a technique for storing a relatively large amount of data in a limited resource.

[0007]

However, even if this data compression is directly applied to the compression of the color conversion table, there is a problem that the effect of the compression does not increase so much.

[0008] That is, data compression is based on the basic method of reducing redundancy based on correlation between data and the like. On the other hand, the table data of the color conversion table is
Normally, the color output device exhibits nonlinear characteristics and has a wide dynamic range of data values. Therefore, the degree of data redundancy tends to be relatively high, such as low correlation between data. Therefore, there is a problem that the compression ratio does not increase even if any compression algorithm is applied.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problem, and an object of the present invention is to enhance the effect of compression when a color conversion table is compressed and stored in a storage medium. It is an object of the present invention to provide a color conversion table storage method and an image processing device that can be used.

[0010]

For this purpose, the present invention provides a color conversion table storing method for compressing data of a color conversion table and storing the data in a storage medium. For each direction of the axis, the table data is rearranged in the direction in which the rate of change of the table data is small, and for the rearranged table data, the axis or the axis parallel to the axis in the direction of the small rate of change Generating a compressed stream by calculating a difference value along a straight line, and performing data compression based on the generated compressed stream.

An image processing apparatus for performing a process of compressing a color conversion table and storing the data in a storage medium,
Rearranging means for rearranging the table data in the direction of the smaller change rate of the table data in the direction of each of the plurality of axes defining the input space of the color conversion table; A compressed stream generating means for generating a compressed stream by calculating a difference value along the axis or a straight line parallel to the axis in the order of smaller direction, and a compressing means for compressing data based on the generated compressed stream. , Are provided.

According to the above configuration, for example, the change rate of the table data is checked in each axis direction of the input space of the color conversion table, and based on this, the table data is rearranged in the direction of the smaller change rate, and Since the rearranged table data is differentiated along an axis having a small rate of change along the axis or a straight line parallel to the axis, and data compression is performed on the differentiated data, the rearrangement causes, for example, The run length of the compression becomes longer, and by differentiating the run length, the degree of redundancy for the compression can be reduced, for example, the correlation between data can be further increased. Can be increased.

[0013]

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

[First Embodiment] FIG. 1 is a main flowchart showing a procedure of a process of storing a color conversion table according to a first embodiment of the present invention.

The color conversion table according to the present embodiment includes R, G,
The three-dimensional space with B as the input axes is the input space,
4 obtained by dividing each axis into 16 equal parts (17 points on each axis)
It has 913 grid points. On the other hand, the output space of this table is arbitrary, but as described above in the conventional example, the table is responsible for converting the output space into an output value that is one scalar. That is, the table is
Table data as the output value is stored for each of the grid points. In the present embodiment, it is assumed that all the table data are 8-bit positive values.

First, in step S100 in FIG.
Then, the change rate of the output value along each axis of the input space or a straight line parallel thereto is examined. This process may be omitted if the relationship between each input axis and the output value is empirically known. For example, when the conversion from the RGB space to another RGB space is considered, it is empirically found that the rate of change becomes larger in the order of B, G, and R in the conversion of (RGB) R. The process of checking the rate can be omitted.

If the relationship of the change rate is unknown at step S100, the change rate can be checked by the processing shown in FIG.

In FIG. 2, steps S201 to S20
In step 5, the rate of change with respect to R is first examined. First, in step S201, constant values b and G are set as the values of B and G, respectively.
A straight line for examining the change rate is set by setting g.
That is, in this case, the R axis or a straight line parallel to the R axis is selected as a straight line for examining the rate of change in accordance with the constant values b and g.

After selecting a straight line, steps S202 to S2
In a loop of 04, a difference value array in the R direction is obtained along this straight line. This difference value array is represented by T [b] [g] [R] -T [b]
[g] [R-1], R = 1, 2,..., 17
That is, the table data of the grid points (b, g, R) and the grid points (b, g, R-1) adjacent to each other on the straight line, that is, the difference between the output values is sequentially calculated, and the array is obtained. .

Next, in step S205, the absolute value of each difference value in the array obtained above is taken and the average thereof is obtained, and the average value is used as the rate of change with respect to R.

When the above-described processing for obtaining the rate of change for R is completed, in the next step S206, the same processing as described above is performed for G and B, and the rate of change for G and B is obtained.

In the above description, an example in which the difference value is obtained along one typical straight line has been described, but the application of the present invention is not limited to this embodiment. For example,
For each of R, G, and B, the rate of change may be determined for a plurality of straight lines along one direction, and the average of the rates may be used as the rate of change. Further, in the above example, the difference was calculated assuming that the interval between the grid points is constant. However, if the interval is not constant, when the difference is calculated in step S203, the difference value divided by the grid point interval is calculated as the grid point. It can be a difference value between them.

Referring again to FIG. 1, step S100
When the rate of change for each axis is determined by the processing of (1), in step S101, the data is rearranged in the order of the axis with the smallest rate of change.

FIG. 3 is a flowchart showing the procedure of the rearrangement process.

For simplification of the description, the above-mentioned step S10
The names of the axes are generalized according to the rate of change obtained by the processing in step 1, and x, y, and z are set in ascending order of the rate of change. For example, Gx, R
It is assumed that the results of y and Bz are obtained.

In this case, in the rearrangement process, the table data before rearrangement is a one-dimensional stream Stream [i
index], and the position index of each table data on the stream with respect to the input (RGB).
x is

[0027]

(Equation 1)

In this case, the data is transferred to a three-dimensional array P [z] [y] [x] prepared in advance.

Specifically, in step S304,
For the rearrangement, the index “index” representing the position on the stream is calculated based on the equation (eq1) and the magnitude relationship between the change rates of the respective axes described above.

[0030]

(Equation 2)

## EQU1 ##

Then, in step S305, the following substitution relation

(Equation 3)

According to the above, the table data is rearranged in the three-dimensional array. As is clear from the above description, the index obtained by the equation (eq2) is always the same as that obtained by the equation (eq1), regardless of the magnitude of the change rate obtained above, and (eq3) In order to clarify the substitution relationship represented by the expression (equation), it is expressed as the expression (eq2) for convenience.

The above processing is performed in steps S301 to S306.
By performing this for all the loops composed of, the rearrangement is completed.

According to this rearrangement, those in which the values of the table data are close in the three-dimensional array are arranged in a concentrated manner. As a result, in data compression, for example, the correlation between data can be increased, and the run length can be lengthened, whereby the compression ratio can be improved.

After the table data is rearranged in step S101 and stored in the three-dimensional array as described above, the index for the offset array is initialized to 0 in step S102 shown in FIG. Note that this sequence is 8b
This is an array having 307 it elements, which is used in data decompression processing described later.

Next step S103, step S104
In the loop constituted by steps S107 to S107, the data that has been rearranged as described above is differentiated along a straight line parallel to the x-axis on a lattice plane parallel to the xy plane.

That is, first, in step S103, a plane z = z0 (0, 1, 2,..., 16) is designated, and then in step S104, y0 (0, 1, 2,..., 16)
Is specified. Accordingly, z which is a straight line on the lattice plane is obtained.
= z0; y = y0 can be specified. Next, in step S105, data difference processing is performed along the specified straight line.

FIG. 4 is a flowchart showing details of this processing.

The array of the difference values to be obtained is a three-dimensional array d [z] [y]
When represented by [x], first, in step S401, data of the start point of the specified straight line is substituted. This process

[0041]

(Equation 4)

Can be expressed as follows. Next, step S4
In 02, a variable m for obtaining the minimum value of the difference data on the straight line is initialized by a value obtained by substituting the above initial value.

Further, at step S403, the value of x is set as a loop counter, and at step S404, the difference value at the set x is calculated by the following equation.

[0044]

(Equation 5)

Is calculated by That is, the processing for obtaining the difference value is sequentially performed between adjacent grid points on the specified straight line. Next, step S
At 405, the minimum value m at that time is compared with the difference value d of the above calculation result, and when d is smaller than m, the minimum value is updated by d.

By the above loop processing, a straight line z = z0;
The difference value array along y = y0 and the minimum value of the array are obtained as follows.

[0047]

(Equation 6)

Next, in step S407, the sign of m is checked. If it is negative, the sign is inverted in step S408, and if it is positive, 0 in step S409.
And Further, in the loop of steps S411 to S414, all the values are converted to positive values by adding the above m to each difference value in the difference value array. Here, when m after sign reversal or the like becomes m> 255, or when at least one d after being converted to a positive value exceeds 255, the process branches in step S410 or S413, and FIG. 1
A failure status is returned to the main routine shown in. In other words, when a negative determination is made in each of the above branching steps, and the process exits the loop processing and reaches step S415,

[0049]

(Equation 7)

That the condition (1) is guaranteed, that is,
It means that all the difference values in the difference value array take values between 0 and 255, and the minimum value m is 255 or less.

Finally, in step S415, the obtained value of m is stored in the offset array offset [o], the index o of the offset array is incremented, and a success status is returned to the main routine.

Referring again to FIG. 1, as a result of the above-described difference processing in step S105, a status indicating success or failure is returned. In step S106, this is determined. When the success status is returned, the process returns to the beginning of the loop from step S107 and the above processing is repeated for other values of z0 and y0, that is, for other straight lines. Then, when the difference processing is successful for all the straight lines, the process exits this loop. As a result, 28
This means that the difference value array and the offset array have been obtained for the nine straight lines. The processing when the failure status is returned will be described later.

When all the differentiating processes have succeeded and the process exits the loop, in the loop composed of steps S108 to S111, y is set in the same manner as in the above-described differential along the x direction.
The difference processing is performed on the straight line in the direction. The target straight line can be expressed as z = z0; x = 0 by z0 set in step S108. Then, in step S109, when the obtained difference value array is d [z0] [y] [0] in the same manner as the processing of step S105 described above,

[0054]

(Equation 8)

The difference is calculated according to the following. In this process, a corresponding offset array is also obtained in the same manner as described in step S105, and (eq 6)
The second expression of the expression is converted to a positive value. This processing is described in FIG.
If the corresponding symbol is replaced in the above, the description of step S105 described above applies as it is, and a detailed description thereof will be omitted.

When the loop of steps S108 to S111 ends without error, finally, in step S112, a difference processing is performed along the z-axis. This step S112
The processing in step S105 and step S109
Is completely equivalent to that in
[z] [0] [0]

[0057]

(Equation 9)

Is as follows. Further, the offset value is also obtained at the same time, and is further converted to a positive value ga of the second equation (eq 7). If there is no error in the processing here, the processing shifts to the processing in step S114 through the determination in step S113.

According to the processing for obtaining the difference value along each straight line in the input space as described above, it is possible to increase the correlation between the data obtained from the difference between the table data. For example, in a straight line having a portion in which the value of the table data changes at a constant rate, the differentiated data d has the same value, and in this portion, the correlation between the data is high, or the occurrence probability of the predetermined data. Can be said to be high. As a result, in combination with the above-described data rearrangement, it is possible to improve the compression ratio in the compression processing described later.

After the difference processing, in step S114,
Generate a data stream for compression. In this case, the processing differs depending on whether all the success / failure determinations in step S106, step S110, and step S113 are successful, and when not.

First, generation of a compression data stream in the former case will be described with reference to FIG.

In the processing shown in FIG. 5, a one-dimensional array having 4912 elements is prepared in advance as a stream for compression, and in step S501, an index index indicating a writing position in this array is initialized to 0. Be transformed into Next, in the loop composed of steps S502 to S508, the difference value array d [z] [y] obtained above is obtained.
Of [x], 4624 elements of difference values corresponding to 289 straight lines parallel to the x-axis are substituted into the stream according to s [index] = (z, y, x).

Next, in the loop composed of steps S509 to S513, the difference value 272 element corresponding to the 17 straight lines parallel to the y-axis is similarly set as s [index] =
Substituted into the stream according to (z, y, 0). Finally, in a loop composed of steps S514 to S516, z
The 16 difference values along the axis are s [index] = (z,
(0,0).

As described above, a data stream of a total of 4912 elements is formed. As shown in (eq 5), since the elements of this stream are all 8-bit positive values, the byte size of the stream is 4912
It becomes bytes.

Next, a description will be given of the processing of step S114 when it is determined that the above-mentioned difference conversion has failed. First, similarly to the above, an array having 4913 elements is prepared in advance as a stream buffer. Next, the contents of the stream on the right side in (eq 3) are copied to a stream prepared in advance, and this is used as compression data. That is, the above-described processing such as rearrangement is ignored, and the input table data is compressed as it is. It should be noted that the stream processing indicated by (eq 3) is omitted by omitting the copy processing to the buffer described above.
Of course, am may be used as it is as a stream for compression. If the dynamic range does not fall within 8 bits as a result of this processing, the effect of almost certainly compressing the data can be expected by compressing the original data without performing rearrangement or differentiation.

When the generation of the compressed stream in step S114 is completed, a compression process is performed on the data of the generated compressed stream in step S115. For the application of the present invention, the compression algorithm used here is arbitrary, and it is only necessary to obtain the compressed data stream and byte size as output. As a compression algorithm, for example, a method called LZ77 method known to those skilled in the art can be used.

Next, in step S116, the total number of bytes of the data after compression is compared with that before compression.
The total number of data before compression is the size of the table itself, and is 17 ³ = 4913 bytes in this example. Further, the total number of data after compression differs depending on whether or not rearrangement is established. If the condition holds, the size of the offset array (= 307 bytes) and d [0] are added to the stream size after compression.
[0] It becomes the value obtained by adding 1 byte of [0], and if not satisfied, it is only the stream size after compression. As a result of these comparisons, if the total number of data after compression is smaller than that before compression, the flow advances to step S117 to set a compression state necessary for decompression described later. Elements necessary for this compression state are: 1. Stream size before compression (= 4913 bytes or 4912 bytes) 2. Stream size after compression 3. Number of elements in offset array 4. Offset array 5. Success or failure of rearrangement 6 . Correspondence of axes before and after rearrangement 7. d [0] [0] [0]. Here, as described in the above item 5, the success or failure of the rearrangement is described. For example, when the number of elements of the offset array is 0, it indicates that the rearrangement was not established. If it is assumed, it can be omitted. The sixth term can be omitted in the same manner if the rearrangement is performed by a fixed method without using the dynamic rearrangement algorithm.

On the other hand, if a negative determination is made in step S116, the state variable is set in step S118 so as to indicate non-compression. For example, if the first and second terms are set to be equal, it is possible to set that compression is not performed. In this case, since the rearrangement does not make sense, in step S119, the stream after compression is replaced with the original data Stream. By this processing, the total number of data after compression is compared with that before compression, and if the former is larger than the latter, the data is stored as it is without compression, so that the adverse effect of expansion due to compression can be prevented.

Finally, in step S120, the above-mentioned state variables and the stream after compression are stored in a predetermined memory, and a series of compression processing ends.

As a result, it is possible to compress the data of the color conversion table at a relatively high compression rate.
The color conversion table can be stored even in a memory having a limited capacity.

When the color conversion table stored as compressed as described above is used for color conversion processing,
It is necessary to use it after extension. The decompression process will be described next.

FIG. 6 is a flowchart showing this heart processing.

In FIG. 6, first, in step S601, a state variable describing the compression state is read. This includes the information of items 1 to 7 set in step S117 described above. Next, step S602
Now, read the compressed data stream. Here, it is assumed that the data is read into the array stream [], as shown in FIG. It should be noted that the array stream [] has, of course, a capacity sufficient to store all the decompressed data. Next, in step S603, it is determined whether the stream has been compressed. As described above, the determination may be based on whether the stream size before compression is equal to that after compression, for example. If it is determined that the data is compressed, the stream is expanded in step S604. On the other hand, if it is determined that the data has not been compressed, the subsequent processing is meaningless and the processing is terminated. The algorithm of the decompression process in step S604 is arbitrary, but it goes without saying that it must be paired with the compression process performed in step S115 in FIG. In the decompression processing of this embodiment, the stream
It is assumed that the compressed data of [] is decompressed and then stored again in stream [] and returned.

Next, in step S605, it is determined whether or not this data has been rearranged at the time of compression. If the data is not sorted, stream
Since [] is in the same state as Stream on the right side in (eq 3), the process ends here.

If the rearrangement has been performed, the process proceeds to step S606 and subsequent steps. In step S606, the value of the origin is stored in d [0] [0] [0]. This has already been read in the state variable reading process in step S601.

After the initialization in step S607, in the loop composed of steps S608 to S612, the difference data sequence in the x direction is copied from the stream to the three-dimensional array d [z] [y] [x]. You. Similarly, in steps S613 to S616, the difference value array in the y-axis direction is read, and in the loop of steps S617 to S619, the difference value array on the z-axis is read. When these series of substitution processes are completed, the state of d [z] [y] [x] becomes (eq 7)
, Which corresponds to the last state that has been converted to a positive value.

The next processing to be performed is to convert the differential state into actual data. In preparation for performing this processing, in step S620, an offset array is read. Then, in step S621, the difference value is converted into actual data using the offset array. This processing will be described with reference to FIG.

In FIG. 7, first, in order to convert data on the z-axis, a necessary offset value is read into a variable in step S701. Next, steps S702 to S702
In the loop constituted by 704, the offset value is subtracted from the array d [z] [0] [0]. This is a process opposite to the positive value conversion performed at the time of compression. Next, steps S705 to S707
Is converted from the difference value into the actual data. This is the reverse process of the process represented by (eq 7). Similarly, in the subsequent processing, all data in the y-axis direction and the x-axis direction are converted.

Referring again to FIG. 6, step S621 is performed.
After the actual data is converted as described above, the last step S
At 622, the original sequence is returned and stored in the stream. This may be performed by performing the reverse process of step S101 in FIG. Now, as a result of analyzing the state variables, when it is assumed that the correspondence of the axes is equivalent to (eq 1) and (eq 2), the rearrangement and the assignment to the stream are performed by the (eq) in step S305 in FIG. 3) The left and right sides are exchanged.

[Second Embodiment] The second embodiment of the present invention is different from the first embodiment only in the difference processing of steps S105, S109 and S112 described in FIG. It is. Accordingly, hereinafter, only the difference processing along the predetermined straight line will be described with reference to the example of the difference processing along the x direction in step S105 in FIG.

FIG. 8 is a flowchart showing this process.

In FIG. 8, first, in step S801,
Then, the starting point of the straight line is substituted into d [z0] [y0] [0]. Next, in steps S802 and S803, the minimum value and the maximum value are respectively set to the numerical values shown in FIG.
Initialized to 128 and 127.

The processing performed on d [] [] [] in the loop composed of steps S804 to S808 is as described in (eq 4) above. In this loop, the maximum value and the minimum value are updated simultaneously with the processing for d. However, as is clear from the above initial value, when the minimum value of the difference value series is larger than -128, min remains the initial value -128. Similarly, when the maximum value of the difference value series is smaller than 127, ma
x is kept at the initial value 127.

From these facts, when the difference value sequence falls within the signed 8-bit value range, in the subsequent processing after branching, the offset value is set to 0 in step S814. Otherwise, if the minimum value is smaller than -128, the maximum value is determined in step S810. If the minimum value is larger than 127, it means that the dynamic range of the difference value series does not fall within 8 bits. Failure status is returned. On the other hand, step S
If the determination in step 810 is negative, the offset value is set to step S8 based on the prediction that the negative value is exceeded.
Set the value of 11. When the minimum value is larger than -128, the maximum value is determined in step S812. When the maximum value is larger than 127, the offset value is set to the offset value based on the prediction that the positive value side is exceeded. The value of S813 is set.

Since the offset value is obtained by the above processing, the difference value array is shifted to the 8-bit value range in the loop from step S815 to S818. By the way, in the above-described processing for obtaining the offset value, it is not accurately determined whether or not the dynamic range of the difference value array falls within the 8-bit range, so that a check is made in step S817. Here, when it is determined that the dynamic range is beyond the 8-bit dynamic range, a failure status is immediately returned, and the process exits. Finally, step S
At 819, the offset value is stored in the array, a success status is returned, and the process is terminated.

[Image Processing Apparatus] FIG. 9 is a diagram showing an embodiment of an image processing system relating to the processing described in the first or second embodiment. The system shown in FIG. 1 includes a personal computer (hereinafter, also simply referred to as “PC”) 1 and a printer 4. The PC 1 and the printer 2 can send and receive print data and control signals via their respective interfaces (I / F) 2 and 3.

An apparatus for performing the processing described in the first or second embodiment is referred to as an image processing apparatus in this specification. Generally, these processes are performed on a PC, but if the printer is configured to be able to perform the processes,
Such a printer is included in the image processing apparatus described above. Further, a storage medium for storing the compressed table is generally provided in a PC, and the PC reads out the stored color conversion table by decompressing the table, and performs a color conversion process using the table. However, also in this case, the printer 4 may have a storage medium for storing the color conversion table, and perform the color conversion process using the table. As the storage medium, for example, a RAM-type memory can be used, but the form is not limited, as is clear from the description of each of the above embodiments.

Further, the form of the printer may be any as long as it has an image forming function, and may be the printer shown in FIG. 9, a copying machine, a facsimile or the like. Further, as the image forming method, an electrophotographic method, an ink jet method, or the like can be used.

[Other Embodiments] In each of the above-described embodiments, two processes of rearranging table data and differentiating the rearranged table data are performed. Although the redundancy of data related to compression is reduced, for example, by increasing the correlation between them, the predetermined effect of the present invention can be obtained by either one of the above two processes. Therefore, data compression including any one of the above processes is also included in the present invention.

[Seventh Embodiment] As described above, the present invention is applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.), and is applied to a single device (for example, a copying machine). , Facsimile machine).

Further, in order to operate the various devices so as to realize the functions of the above-described embodiments, the devices connected to the various devices or the computers in the system are connected to the above-described FIG. 1, FIG. 2, FIG. 4, FIG. 5, FIG. 6, FIG.
A program executed by supplying a program code of software for realizing the functions of the embodiment shown in FIG. 8 and operating a computer (CPU or MPU) of the system or the apparatus according to a stored program to operate the various devices. Are also included in the scope of the present invention.

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

Examples of storage media for storing such program codes include a floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, and 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 embodiment are realized, but also the OS (Operating System) running on the computer or another program. 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 the computer or a function expansion unit connected to the computer, and then, based on the instruction of the program code, the function expansion board or the function expansion unit. It is needless to say that the present invention includes a case where the CPU or the like provided in the first embodiment performs a part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

[0096]

As described above, according to the present invention,
For each axis direction of the input space of the color conversion table, for example, the rate of change of table data is checked, and based on this,
The table data is rearranged in the direction of the smaller change rate, and the rearranged table data is differentiated along the axis having the smaller change rate along the axis or a straight line parallel to the axis. Since the data compression is performed, the rearrangement increases the run length of the compression, for example, and the degree of the redundancy of the compression such as the correlation between the data can be further increased by differentiating the run length. It is possible to reduce the data compression ratio, thereby increasing the compression ratio in data compression.

As a result, when the above-mentioned LZ77 method, which is a general compression technique, is applied to a color conversion table for a color printer composed of, for example, 4913 points of data, the compression ratio is improved by about 40%.

The reason why the compression ratio is improved will be described with reference to a simple model. Now, suppose that two-dimensional table data is considered, and that the characteristics of the data change linearly with respect to X and Y, and have a larger inclination with respect to the X direction. When this data is replaced with a one-dimensional stream, the time-series change of the stream is as shown in FIG. In the same figure, the upper part scans the X-axis first, and then scans in the Y-axis direction, and the lower part shows the opposite case. (Here, T is the number of data on each axis, and N is the index of the stream.) As is clear from the figure, the data series in the upper row saturates faster, so a constant value is obtained when the difference is calculated. Becomes shorter than that of the lower row. According to the principle of LZ77 compression, the longer the repetition length of a certain pattern, the higher the compression ratio. Therefore, it is considered that the lower series is more easily compressed than the upper series. Of course, the actual data series is more complicated, and the data does not become a completely linear function. Conceivable.
Here, the LZ77 compression is taken as an example, but the analysis by the above-described model is naturally applicable to other compression methods such as run-length compression.

[Brief description of the drawings]

FIG. 1 is a flowchart illustrating a main process of storing color conversion table data by data compression according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating a process of calculating a change rate of a table output value along an axial direction of an input space of a color conversion table in the process illustrated in FIG. 1;

FIG. 3 is a flowchart showing a process of rearranging table data in the order of the axis having the smallest change rate in the process shown in FIG. 1;

FIG. 4 is a flowchart showing a process of converting the rearranged data into a positive value after subtracting the rearranged data along a straight line parallel to the axis in the process shown in FIG. 1;

FIG. 5 is a flowchart showing a process of generating a data stream for compression in the process shown in FIG. 1;

FIG. 6 is a flowchart showing a process of expanding and reading out a color conversion table stored after being compressed by the process of FIG. 1;

7 is a flowchart showing a process of returning difference data to actual data in the decompression process shown in FIG.

FIG. 8 is a flowchart showing a process of converting the rearranged data into a signed 8-bit value after differentiating the rearranged data along a straight line parallel to the axis according to the second embodiment of the present invention.

FIG. 9 is a block diagram illustrating a configuration of an image processing system related to execution of a data compression process according to the first or second embodiment.

FIG. 10 is a diagram for modeling and explaining the principle of the improvement of the compression ratio provided by the present invention.

[Explanation of symbols]

 1 PC 4 Printer

Claims (16)

[Claims] 1. A color conversion table storage method for compressing data of a color conversion table and storing the data in a storage medium, wherein the direction of each of a plurality of axes defining an input space of the color conversion table is stored in the table. The table data is rearranged in the direction of the smaller change rate, and the rearranged table data is compressed by obtaining the difference value along the axis or a straight line parallel to the axis in the direction of the smaller change rate. Generating a stream, and compressing the data based on the generated compressed stream. 2. The method according to claim 1, wherein the step of rearranging the table data in the direction in which the rate of change is small includes obtaining a rate of change of at least one straight line parallel to the axis for each of the axes; 2. The color conversion table storage method according to claim 1, wherein the order of the rearrangement is determined according to the magnitude of the absolute value of the ratio. 3. The axis in the direction of the smaller change rate,
Alternatively, the step of obtaining a difference value along a straight line parallel to the axis is as follows: when the input space is three-dimensional and axes in the direction are x, y, x in ascending order of change, Find the difference value for all the straight lines parallel to the axis,
Next, a difference value is obtained for the y-axis on each z-plane.
3. The color conversion table storage method according to claim 1, wherein a difference value on the z-axis is obtained, and the compressed stream is generated in this order. 4. The axis in the direction in which the rate of change is small,
Alternatively, the step of obtaining the difference value along a straight line parallel to the axis includes, when the differentiated data exceeds a predetermined dynamic range, canceling the rearrangement and the step of obtaining the difference value, and canceling the original table data. The color conversion table storage method according to any one of claims 1 to 3, wherein the color conversion table is directly output to the compressed stream. 5. The data compressing step compares the data amount before and after the compression, and when the data after the compression is larger than that before the compression, stops the compression and stores the original table data. 5. The color conversion table storage method according to claim 1, further comprising the step of: 6. A color conversion table storing method for compressing data of a color conversion table and storing the data in a storage medium, wherein the direction of each of a plurality of axes defining an input space of the color conversion table is stored in the table. Rearranging the table data in the direction of the smaller change rate, generating a compressed stream with respect to the rearranged table data, and compressing the data based on the generated compressed stream. Color conversion table storage method. 7. A color conversion table storage method for compressing data of a color conversion table and storing the compressed data in a storage medium, wherein the direction of each of a plurality of axes defining an input space of the color conversion table is stored in the table data. Generating a compressed stream by obtaining a difference value along the axis or a straight line parallel to the axis in the direction of the smaller change rate, and performing data compression based on the generated compressed stream. A color conversion table storing method. 8. An image processing apparatus for performing a process of compressing a color conversion table and storing the data in a storage medium, wherein the change of the table data is performed for each of a plurality of axes defining an input space of the color conversion table. Reordering means for rearranging the table data in the direction of the smaller rate; and obtaining the difference value of the rearranged table data along the axis or a straight line parallel to the axis in the direction of the smaller change rate. An image processing apparatus comprising: a compressed stream generating unit that generates a compressed stream by using the generated compressed stream; and a compressing unit that compresses data based on the generated compressed stream. 9. The reordering means obtains a rate of change of at least one straight line parallel to the axis for each of the axes, and performs reordering according to a magnitude of an absolute value of the obtained rate of change of the axis. The image processing apparatus according to claim 8, wherein the order is determined. 10. The compressed stream generating means, when the input space is three-dimensional and the axes in the direction are x, y, x in ascending order of change, first, a straight line parallel to the x-axis. The method of claim 1, further comprising: obtaining a difference value for all of them; then obtaining a difference value for the y-axis on each z-plane; finally obtaining a difference value for the z-axis; and generating the compressed stream in this order. 10. The image processing apparatus according to 8 or 9. 11. The compressed stream generating means, when the difference data exceeds a predetermined dynamic range, stops the rearrangement by the rearranging means and the processing for obtaining the difference value, and converts the original table data. The image processing apparatus according to claim 8, wherein the image is directly output to a compressed stream. 12. The compression means compares the data amount before and after the compression, and when the data after compression is larger than that before compression, stops the compression and stores the original table data. The image processing apparatus according to claim 8, further comprising: 13. An image processing apparatus for performing a process of compressing data of a color conversion table and storing the data in a storage medium, wherein a change in the table data is obtained for each of a plurality of axes defining an input space of the color conversion table. Rearranging means for rearranging the table data in the order of decreasing rate, a compressed stream generating means for generating a compressed stream for the rearranged table data, and a compressing means for compressing data based on the generated compressed stream An image processing apparatus comprising: 14. An image processing apparatus for performing a process of compressing a color conversion table and storing the data in a storage medium, wherein the change of the table data is performed for each of a plurality of axes defining an input space of the color conversion table. Compressed stream generating means for generating a compressed stream by calculating a difference value along the axis or a straight line parallel to the axis in the order of decreasing rate; and compressing means for compressing data based on the generated compressed stream. And a color conversion table storing method. 15. An image processing apparatus for generating image data using a color conversion table, comprising: a color conversion table storing process for compressing the color conversion table and storing the compressed data in a storage medium; For each direction of a plurality of axes that define the input space of the table data, the table data is rearranged in the direction in which the change rate of the table data is small. ,
Or a storage medium storing compressed data by processing having a step of generating a compressed stream by calculating a difference value along a straight line parallel to the axis and compressing the data based on the generated compressed stream. And reproducing the color conversion table by reading out the stored data from the storage medium by expanding the image data, and generating image data using the reproduced color conversion table. apparatus. 16. A storage medium storing a program readable by an information processing device, wherein the program is a color conversion table storing process for compressing a color conversion table and storing the data in the storage medium, For each direction of the plurality of axes that define the input space of the color conversion table, the table data is rearranged in the direction in which the rate of change of the table data is small. Generating a compressed stream by sequentially calculating a difference value along the axis or a straight line parallel to the axis, and performing a data compression based on the generated compressed stream. Storage media.