JP2002368994A - Image processor, image processing method and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processor where the substantial number of gradations is increased and the texture reproducing characteristic of a reproduced image is improved by distributing resolution information to gradation information without cutting a useful spatial frequency component based on the local characteristic of image data, and to provide an image processing method and a recording medium. SOLUTION: A gradation/resolution information generating part 401 generates information showing the priority of gradation information and resolution information for each pixel based on the local characteristic of input image data of eight bits. A gradation/resolution information control part 404 distributes resolution information to gradation information again from information showing priority and converts the bit size of pixel data into 12 bits based on re-distributed gradation information. A color matching processing part 404 matches colors by using 12 bits pixel data. An ink color conversion processing part 405 converts data into the color material color of a printer by using 12 bits data which is color-matched. A halftone processing part 406 converts 12 bits data converted into color material color into the number of bits that can be printed by the printer.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an image processing apparatus and method for an image input / output device such as a scanner, a digital camera, and a printer, and a recording medium. In particular, the present invention relates to an image processing technique for increasing the amount of gradation information included in image data and improving the texture reproduction characteristics of the image data.

[0002]

2. Description of the Related Art In recent years, in order to improve the texture reproduction characteristics of image data in image input / output devices such as scanners, digital cameras, and printers, devices and image processing techniques for improving gradation characteristics or resolution characteristics have been actively developed. Is underway. In particular, as a device for improving the gradation characteristics, a dramatic improvement is realized by selectively using light ink and dark ink in an ink jet printer. Further, in the internal image processing system, by increasing the number of bits of the image data, the calculation accuracy is increased and the gradation /
Resolution information is stored. As a method of increasing the number of bits, there are a method of simply increasing the number of bits and a method of using information of peripheral pixels such as a 3 × 3 filter.

FIG. 1 is a diagram showing filter coefficients of a 3 × 3 filter. A method for increasing the number of bits using the filter coefficient will be described. Here, assuming that the pixel value of interest on the i-th row and the j-th column expressed by 8 bits is P (i, j) and the pixel value after the filtering process is P ′ (i, j), P ′ (i, j) ) = (A1P (i-1, j-1) + a2P (i-1, j) + a3P (i-1, j + 1) + a4P (i, j-1) + a5P (i, j) + a6 · P (i, j + 1) + a7 · P (i + 1, j-1) + a8 · P (i + 1, j) + a9 · P (i + 1, j + 1)) / sum1 (1) where sum1 = a1 + a2 + a3 + a4 + a5 + a6 + a7 + a8 + a9 (2) As a filter coefficient having a low-pass frequency characteristic, there is an example in which coefficients a1 to a9 are set to coefficients as shown in FIG. 2 and used.

[0004] After the calculation processing of the equation (1), the number of necessary bits of P '(i, j) is converted to a substantial number of gradations.

[0005]

However, in the above-mentioned conventional example, a substantial increase in the number of gray scales cannot be realized by simply increasing the number of bits. In addition, the method using a 3 × 3 filter having low-pass frequency characteristics can substantially increase the number of tones, but since low-pass filtering is performed, usefulness of the target image data is improved. However, there is a problem that the spatial frequency component, that is, the resolution information is also cut, and it is not possible to improve the texture reproduction characteristics of the reproduced image.

SUMMARY OF THE INVENTION An object of the present invention is to solve the above-described problem. Resolution information is converted into gradation information based on local characteristics of image data without cutting useful spatial frequency components. It is an object of the present invention to provide an image processing apparatus and method, and a recording medium, in which the number of gradations is substantially increased by distributing and the texture reproduction characteristics of a reproduced image are improved.

Another object of the present invention is to distribute the resolution information to the gradation information based on the local characteristics of the image data without cutting useful spatial frequency components, thereby obtaining a numerical gradation. In addition to increasing the number of colors, applying a material that can expand the color reproduction range, such as color formers and brighteners, increases the dynamic range of color reproduction, realizes a substantial increase in the number of gradations, and enhances the texture of reproduced images. It is an object of the present invention to provide an image processing apparatus and method and a recording medium that realize improved reproduction characteristics.

[0008]

In order to achieve the above-mentioned object, an image processing apparatus according to the present invention provides a method of setting priority of gradation information and resolution information for each pixel based on local characteristics of N-bit input image data. Generating means for generating information indicating the resolution, redistribution means for redistributing resolution information to the grayscale information based on the grayscale information for each pixel and information indicating the priority of the resolution information, and the redistributed grayscale. Converting means for converting the bit size of the pixel data into M (M> N) bits based on the information.

According to another aspect of the present invention, there is provided an image processing method comprising the steps of: providing information indicating priority of gradation information and resolution information for each pixel based on local characteristics of N-bit input image data; A generation step of generating, a redistribution step of redistributing resolution information to gradation information based on the gradation information of each pixel and information indicating a priority of the resolution information, and a pixel based on the redistributed gradation information. When the bit size of data is M (M
> N) a conversion step of converting the bits into bits.

[0010]

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

[First Embodiment] FIG. 3 is a diagram showing a system configuration according to the first embodiment. In FIG. 1, reference numeral 301 denotes a computer which holds color image data composed of red (R), green (G), and blue (B) input from an image reading device (not shown) or an external device via a network. Is transmitted to a color monitor or a color printer described later. 302 is a color monitor,
The color image data from the computer 301 is displayed. Reference numeral 303 denotes a color printer, which is a computer
The reproduction of the color image data sent from step 1 is performed.

FIG. 4 is a block diagram showing the configuration of the image processing apparatus according to the first embodiment. This image processing apparatus is mounted on a color printer 303 shown in FIG.
An image processing system for printing color image data held on the computer 301 by the color printer 303.

Referring to FIG. 4, reference numeral 401 denotes a gradation / resolution information generation unit which generates information indicating the priority of the gradation / resolution in accordance with the local characteristics of the input image data. The output data from the gradation / resolution information generation unit 401 is composed of 8 bits. The larger the output value, the higher the priority of the gradation information, and the smaller the output value, the higher the priority of the resolution information. Reference numeral 402 denotes a gradation / resolution information table creation unit that creates a gradation / resolution information table output to the gradation / resolution information generation unit 401. Reference numeral 403 denotes a gradation / resolution information control unit, and a gradation / resolution information generation unit 401
, The resolution information is redistributed to the gradation information based on the information indicating the priority of the gradation / resolution outputted from the CPU, the input image data is converted from 8 bits to 12 bits, and the substantial number of gradations is increased. I do.

Reference numeral 404 denotes a color matching processing unit.
Based on the profile information of the input image data and the profile information of the target color printer, the colors of the reproduced image are matched. An ink color conversion processing unit 405 converts the input color image data into a color material color (CMYK) of a target color printer. A halftone processing unit 406 performs halftone processing according to the number of printable bits of the target color printer. The 1-bit C'M'Y'K 'data processed by the halftone processing unit 406 is printed using the color printer 303, and the image data is reproduced.

Reference numeral 407 denotes a CPU, which is a controller for controlling the image processing apparatus. Reference numeral 408 denotes a ROM, which is a memory that stores a control program and control data of the CPU 407. 409 is a RAM, and the CPU 40
Reference numeral 7 denotes a memory in which a work area, various tables, and the like used when executing processing according to the program stored in the ROM 408 are defined.

In the first embodiment, the gradation / resolution information generation unit 401 and the gradation / resolution information table generation unit 40
2, and the three blocks of the gradation / resolution information control unit 403 substantially distribute the resolution information to the gradation information without cutting useful spatial frequency components based on local characteristics of the image data. The number of gradations can be increased to improve the texture reproduction characteristics of the reproduced image.

Hereinafter, with reference to FIG. 5 and subsequent drawings, detailed processing contents of the above-described blocks 401, 402, and 403 will be described.

In FIG. 5, a CPU 407, a ROM 40
8. The RAM 409 is the same as that in FIG. 4 and controls the setting of necessary parameters, the arithmetic processing, and the like in each block in FIG.

A gradation / resolution information generation unit 401 shown in FIG.
Reference numeral 501 denotes a luminance calculation unit, which is a block for converting RGB input pixel data into luminance information. 50
Reference numeral 2 denotes a spatial frequency characteristic detecting unit which detects spatial frequency characteristics in a target 3 × 3 block based on luminance information from the luminance calculating unit 501. An average luminance calculation unit 503 is a block that calculates the average luminance of a target 3 × 3 block based on the luminance information from the luminance calculation unit 501. Reference numeral 504 denotes a filter coefficient α table unit which executes a table process for deriving a filter coefficient α from the spatial frequency value from the spatial frequency characteristic detecting unit 502 and the luminance value from the average luminance calculating unit 503. The derived α value is transferred to the gradation / resolution information control unit 403.

On the other hand, in the gradation / resolution information control section 403, reference numeral 505 denotes a 3 × 3 basic filter table section.
A basic table of × 3 blocks is stored, and a new 3 × 3 filter coefficient is calculated based on the output value α from the filter coefficient α table 504. 506 is 3 × 3
The filter operation unit stores a new 3 × 3 filter coefficient, performs a filtering process based on the new filter coefficient, and executes a bit number conversion process.

In the gradation / resolution information table creating unit 402, a filter coefficient α table calculating unit 511 is a highlight filter characteristic table unit set in 507 by the CPU 407, ROM 408, and RAM 409, and an intermediate luminance filter 508 in 508. Characteristic table section, shadow filter characteristic table section of 509, 51
A filter coefficient α table is calculated based on the data of the 0 luminance direction interpolation coefficient table section. Note that the calculated filter coefficient α is stored in the filter coefficient α table unit 504 of the gradation / resolution information generation unit 401.

Next, the specific processing contents of each block will be sequentially described. First, in the luminance calculation unit 501, the luminance
Y (i, j) is calculated based on the following equation.

Y (i, j) = b1 × R (i, j) + b2 × G (i, j) + b3 × B (i, j) (3) where b1, b2, and b3 are obtained from the RGB data. This is a coefficient for obtaining luminance.

The spatial frequency characteristic detecting section 502 detects the spatial frequency F (i, j) using the luminance value for each 3 × 3 block centering on the target pixel. The spatial frequency F (i, j) of this 3 × 3 block is given by: Y (i, j)
It is obtained from the largest value among the absolute values of the differences between the luminance values of (i, j) and the eight peripheral pixels shown below.

Y (i-1, j-1), Y (i-1, j), Y (i-1, j + 1), Y (i, j-
1), Y (i, j + 1), Y (i + 1, j-1), Y (i + 1, j), Y (i + 1, j-1) , The average value of the luminance values of the nine pixels of the target 3 × 3 block is determined. The filter coefficient α table unit 504 includes a two-dimensional table of spatial frequencies and luminance values as shown in FIG. In this two-dimensional table, 8-bit values from 0 to 255 indicating the filter coefficient α are stored. The larger the value, the higher the priority of the gradation. This means that conversion processing is performed.

Next, a 3 × 3 basic filter table section 5
05, a basic 3 × 3 filter coefficient as shown in FIG. 1 is multiplied by a filter coefficient indicating the priority of gradation / resolution as shown in FIG. Calculate and the result is 3 × 3 filter operation unit 5
06.

Here, the 3 × 3 filter coefficient shown in FIG. 1 is a coefficient that defines a two-dimensional frequency characteristic in the vertical and horizontal directions, and for example, by using the coefficient as shown in FIG. A 3 × 3 filter having characteristics can be set.

Β in FIG. 7 is obtained by the following equation.
By the α value from the filter coefficient α table unit 504,
The ratio between the target pixel and the peripheral pixels can be determined.

Β = 510−α (4) Next, the 3 × 3 filter calculation unit 506 converts the R (red) data of the pixel in the i-th row and j-th column into R (i, j), as in the equation (1). ),
Assuming that the value after the filter processing is R ′ (i, j), R ′ (i, j) = (α · a1 · R (i−1, j−1) + α · a2 · R (i−1, j) ) + Α ・ a3 ・ R (i-1, j + 1) + α ・ a4 ・ R (i, j-1) + β ・ a5 ・ R (i, j) + α ・ a6 ・ R (i, j + 1) + α・ A7 ・ R (i + 1, j-1) + α ・ a8 ・ R (i + 1, j) + α ・ a9 ・ R (i + 1, j + 1)) / sum2… (5) where sum2 = α · a1 + α · a2 + α · a3 + α · a4 + β · a5 + α · a6 + α · a7 + α · a8 + α · a9 (6) G (green) other than R, that is, G (i,
j) and B (blue), that is, the same processing is performed for B (i, j).

Then, the processing is completed by converting R '(i, j) into a 12-bit number.

As is apparent from the above equations (4) and (5), α
In the case of = 0, β = 510. At this time, a flat frequency characteristic is obtained in all frequency regions, and the value of the peripheral pixels is not affected. Not lost at all.

On the other hand, when α = 255, β = 255, and the frequency characteristic of the low-pass filter stored in the 3 × 3 basic table is obtained. , High frequency components are cut and resolution information is lost.

Therefore, by setting the optimum α value based on the local frequency characteristics near the pixel of interest and the average luminance, the gradation is improved without losing effective frequency components, ie, resolution information. It is possible to improve the texture reproduction characteristics of the reproduced image.

Next, the filter coefficient α table section 504
The setting method will be specifically described.

In order to create a two-dimensional filter coefficient α table as shown in FIG. 6, a highlight filter characteristic table section 507 for defining a highlight filter characteristic with respect to a spatial frequency and an intermediate luminance with respect to a spatial frequency are provided. Three one-dimensional tables of an intermediate luminance filter characteristic table unit 508 for defining filter characteristics, a shadow filter characteristic table unit 509 for defining a filter characteristic of a shadow with respect to a spatial frequency, and interpolation in the luminance direction based on the three one-dimensional tables. Perform the processing,
The calculation is performed using a total of four one-dimensional tables of a luminance direction interpolation coefficient table unit 510 for calculating the filter coefficient α of the luminance during that time.

FIGS. 9 to 11 show examples of the filter characteristic tables in the highlight filter characteristic table 507, the intermediate luminance filter characteristic table 508, and the shadow filter characteristic table 509, respectively. FIG. 12 is a diagram illustrating an example of a luminance direction interpolation coefficient table in the luminance direction interpolation coefficient table unit 510.

FIG. 13 is a diagram showing the relationship between four one-dimensional tables and two-dimensional filter coefficient α tables. As shown in FIG. 13, each of the three tables of the highlight filter characteristic table, the intermediate luminance filter characteristic table, and the shadow filter characteristic table has 25 tables.
It shows the actual values stored in the filter coefficient α table of the luminance values of 5, 128, 0.

The filter coefficient α table calculation unit 511 calculates the filter coefficient α between the four one-dimensional tables based on the following equation. The spatial frequency is x (0 ≦ x ≦ 255), the luminance value is y (0 ≦ y ≦ 255), the two-dimensional filter coefficient is α (x, y), the highlight filter characteristic table is H (x), the intermediate luminance Filter characteristic table
If M (x), the shadow filter characteristic table is S (x), and the luminance direction interpolation coefficient table is I (y), the filter coefficient α
(x, y) can be obtained by the following equation.

Α (x, y) = {(255−I (y)) · H (x) + I (y) · M (x)} / 255 where 128 <y <255 {(255−I (y )) · S (x) + I (y) · M (x)} / 255 where 0 <y <128 (7) For example, using FIGS. 9 to 12, α (64,160) = {(25
5-128) ・ 140 ＋ 128 ・ 0} / 255 ≒ 70 ... (8) The filter characteristic tables of FIGS. 9 and 11 show the filter characteristics giving priority to gradation, and the filter characteristics of FIG. 10 show the filter characteristics giving priority to resolution. Therefore, by using the set values of FIGS. 9 to 12, the highlight and the shadow are allocated to the gray scale by distributing the information amount of the resolution to the gray scale with respect to the image of the intermediate luminance. And the improvement of the texture reproduction characteristics of the reproduced image can be achieved.

[Second Embodiment] Next, a second embodiment according to the present invention will be described in detail with reference to the drawings.

In the first embodiment described above, an example in which an image processing system for printing the RGB image data held on the computer 301 shown in FIG. As explained in
A case where the present invention is implemented by software will be described as a second embodiment.

FIG. 14 is a flowchart when the image processing system is implemented by software. First, step S
In step 1401, a two-dimensional filter coefficient α table setting process as shown in FIG. 6 is executed. The detailed processing in step S1401 will be further described later with reference to FIG. Next, in step S1402,
The 3 × 3 basic filter table as shown in FIG. 1 is set, and the processes of the target RGB image data are sequentially executed in a closed loop from step S1403 to S1407, and transferred to a color printer for printing. I do.

In step S1403, step S
A filter coefficient α table set in 1401;
A 3 × 3 filtering process and a gradation / resolution information control process are executed using the 3 × 3 basic filter table set in step S1402. Next, in step S1404, based on the profile information of the image data and the profile information of the target color printer, a color matching process for matching the tint of the reproduced image is executed. In step S1405, an ink separation process is performed to convert the color material into a color material color of the target color printer. Next, step S140
In step 6, halftone (halftone) processing corresponding to the number of printable bits of the target color printer is executed. In step S1407, it is determined whether or not unprocessed pixel data exists.
In the case of s), the process returns to step S1403, and step S1
The processing from 403 to step S1407 is repeated. If the image does not exist (No), all image processing ends.

FIG. 15 is a detailed flowchart showing the setting of the filter coefficient α table shown in FIG. 14 (S1401). First, in step S1501, a highlight filter characteristic table having characteristics as shown in FIG. 9 is set. Then, in step S1502, an intermediate luminance filter characteristic table having characteristics as shown in FIG. 10 is set. Next, in step S1503, a shadow filter characteristic table having characteristics as shown in FIG. 11 is set.

Finally, in step S1504, a luminance direction interpolation coefficient table having characteristics as shown in FIG. 12 is set. In step S1505, a two-dimensional filter coefficient α table is calculated using the tables set in steps S1501 to S1504, and the filter coefficient α table setting process ends. Note that this calculation method is the same as that shown by the equation (7) in the first embodiment.

FIG. 16 is a detailed flowchart showing the gradation / resolution information control processing (S1403) shown in FIG. This processing is to perform gradation / resolution information control processing of sequentially input RGB pixel data. First,
In step S1601, a process of calculating the luminance of the input RGB pixel data using the equation (3) in the first embodiment is executed. Next, in step S1602, the spatial frequency F (i, j) is detected using the luminance value for each 3 × 3 block centered on the target pixel. The spatial frequency F (i, j) of the 3 × 3 block is the difference between the luminance value of Y (i, j) and the luminance values of the eight peripheral pixels shown below, where Y (i, j) is the luminance of the target pixel. Is determined by the largest value of the absolute values of

Y (i-1, j-1), Y (i-1, j), Y (i-1, j + 1), Y (i, j-
1), Y (i, j + 1), Y (i + 1, j-1), Y (i + 1, j), Y (i + 1, j-1) Next, in step S1603, 3 × 3
The average value of the luminance values of the nine pixels of the block is obtained. And
In step S1604, the above-described step S160
The filter coefficient α is selected from the filter coefficient α table set in step S1601, using the spatial frequency detected in step 2 and the luminance value calculated in step S1603. Next, in step S1605,
8 is obtained by multiplying the 3 × 3 basic filter coefficient (see FIG. 1) set in step S1402 by the 3 × 3 filter (see FIG. 7) based on the filter coefficient α selected in step S1604. Calculation of such a 3 × 3 filter coefficient is performed. Next, in step S1606, the filtering process represented by Expression (5) in the first embodiment is performed. In step S1607, the result processed in step S1606 is converted into 12 bits, and the gradation / resolution information control processing ends.

Third Embodiment Next, a third embodiment according to the present invention will be described in detail with reference to the drawings.

In the third embodiment, in the color printer having the system configuration in the first embodiment described above,
Applying materials that can expand the color reproduction range, such as color formers and gloss agents, expands the dynamic range of color reproduction, realizes a substantial increase in the number of gradations, and improves the texture reproduction characteristics of reproduced images. It was made.

FIG. 17 is a diagram showing a system configuration according to the third embodiment. The computer 1701 and the color monitor 1702 shown in the figure correspond to the computer 301 and the color monitor 302 in FIG. 1 described in the first embodiment, and a description thereof will be omitted.

In FIG. 17, reference numeral 1703 denotes a color printer according to the third embodiment, which is provided with a material tank 1704 of the color printer. Specifically, cyan, magenta, yellow for reproducing colors from the left,
A black ink tank and a tank for storing a glossing agent or a coloring agent for expanding the color reproduction range of the color printer and realizing a substantial increase in the number of gradations are provided.

FIG. 18 is a block diagram showing the configuration of the image processing apparatus according to the third embodiment. In the figure, a gradation / resolution information generation unit 1801, a gradation / resolution information table preparation unit 1802, a gradation / resolution information control unit 1803, a color matching processing unit 1804, and an ink color conversion processing unit 18
05, CPU 1807, ROM 1808, and RAM1
Reference numeral 809 denotes 4 in FIG. 4 described in the first embodiment.
01 to 405, 407 to 409,
The description is omitted.

In FIG. 18, reference numeral 1806 denotes a halftone processing unit according to the third embodiment, which is based on information indicating the priority of gradation / resolution represented by 8 bits from the gradation / resolution information generation unit 1801. And halftone information for applying a glossing agent and a coloring agent for substantially increasing the number of gradations. The 1-bit C'M'Y'K 'data processed by the halftone processing unit 1806, the glossing agent, and the coloring agent are printed using the ink tank 1704 of the color printer 1703, and the image data is reproduced. You.

As described above, according to the third embodiment, in addition to the above-described first embodiment, based on information indicating the priority of gradation / resolution, a color printer color such as a coloring agent or a glossing agent is used. By applying a material capable of expanding the reproduction range, the dynamic range of color reproduction can be increased, the number of gradations can be substantially increased, and the texture reproduction characteristics of the reproduced image can be improved.

The detailed configurations of the gradation / resolution information generation unit 1801, gradation / resolution information table preparation unit 1802, and gradation / resolution information control unit 1803 are the same as those of the first embodiment described with reference to FIG. This is the same as the embodiment, and the description is omitted.

FIG. 19 shows an example of a highlight filter characteristic table in the third embodiment, and FIG. 20 shows an example of a shadow filter characteristic table. Note that the intermediate luminance filter characteristic table is the same as that in FIG.

Using this table, the filter coefficient α (x, y) is as follows.

Α (64,192) = {(255−128) · 64 + 128 · 0} / 255 ≒ 32 (9) As described above, according to the third embodiment, the reproduction is performed in the same manner as in the first embodiment. It is possible to achieve an improvement in image texture reproduction characteristics.

[Modifications] In the first to third embodiments,
As a 3 × 3 basic filter table, a 3 × 3 low-pass filter having coefficients as shown in FIG. 2 was used.
The filter coefficient used in the basic filter table is not limited to this, but may be any as long as it has low-pass frequency characteristics. Further, the block size of 3 × 3 is used as the block size for the filtering process, but the present invention is not limited to this, and the process can be similarly performed with an N × N block size.

In the first to third embodiments, the detection of the spatial frequency characteristic and the calculation of the average luminance are executed in units of 3 × 3 blocks. However, these processing blocks are also limited to 3 × 3 blocks. Instead, a block size such as an M × M block may be set freely, and the detection of the spatial frequency characteristics near the target pixel and the calculation of the average luminance may be executed. Also,
In the detection of the spatial frequency characteristic and the calculation of the average luminance, the luminance value is used. However, the detection and the calculation are not limited to the luminance value, and may be any as long as they indicate the brightness.

Further, in the first to third embodiments, the spatial frequency characteristic is defined by using the maximum value of the difference between the luminance component of the target pixel and the peripheral pixel for detecting the spatial frequency characteristic. The detection method is not limited to this, and other methods may be used as long as the frequency characteristics near the target pixel are obtained, such as obtaining the frequency characteristics after spatial frequency conversion using FFT or the like.

Further, in the first to third embodiments, the system configuration as shown in FIGS. 3 and 17 is used. However, the scope of the present invention is not limited to this. The present invention can be applied to any image processing unit such as an image processing unit in a data input device and application software for processing image data.

Further, in the third embodiment, in addition to cyan, magenta, yellow, and black inks for reproducing colors, the color reproduction range of a color printer is expanded to realize a substantial increase in the number of gradations. For this purpose, brighteners and color formers were used. However, these materials are not limited to two types. For example, oil for improving the fixability in electrophotography can be used to expand the color reproduction range of a color printer. Any material can be used as long as it can substantially increase the number of gradations.

In the third embodiment, as in the first embodiment, the image processing system can be implemented by software of the second embodiment.
In this case, by executing the processing in accordance with the flowcharts shown in FIGS. 14 to 16, the same effect as in the case where the processing is executed by hardware can be obtained.

Even if 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.), an apparatus (for example, a copier, a facsimile) comprising one device Device).

Further, an object of the present invention is to supply a storage medium storing a program code of software for realizing the functions of the above-described embodiment to a system or an apparatus, and to provide a computer (CPU or MP) of the system or apparatus.
It goes without saying that U) is also achieved by reading and executing the program code stored in the storage medium.

In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk,
Hard disk, optical disk, magneto-optical disk, CD-
A ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, and the like can be used.

When the computer executes the readout program code, not only the functions of the above-described embodiment are realized, but also the OS (Operating System) running on the computer based on the instruction of the program code. ) May perform some or all of the actual processing, and the processing may realize the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written into a memory provided on a function expansion board inserted into the computer or a function expansion unit connected to the computer, based on the instruction of the program code, It goes without saying that the CPU included in the function expansion board or the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

[0071]

As described above, according to the present invention,
Based on the local characteristics of the image data, the resolution information is distributed to the gradation information without cutting useful spatial frequency components, thereby increasing the actual number of gradations and improving the texture reproduction characteristics of the reproduced image. Can be realized.

Further, based on information indicating the priority of gradation / resolution, a material capable of expanding the color reproduction range of a color printer, such as a coloring agent or a glossing agent, is applied to increase the dynamic range of color reproduction. It is possible to realize a substantial increase in the number of gradations and to improve the texture reproduction characteristics of the reproduced image.

[Brief description of the drawings]

FIG. 1 is a diagram showing filter coefficients of a 3 × 3 filter.

FIG. 2 is a diagram illustrating a filter coefficient having a low-pass frequency characteristic.

FIG. 3 is a diagram illustrating a system configuration according to the first embodiment.

FIG. 4 is a block diagram illustrating a configuration of an image processing apparatus according to the first embodiment.

FIG. 5 is a block diagram showing details of a gradation / resolution information generation unit 401, a gradation / resolution information table creation unit 402, and a gradation / resolution information control unit 403 shown in FIG.

FIG. 6 is a diagram showing a configuration of a two-dimensional table of spatial frequencies and luminance values.

FIG. 7 is a diagram showing 3 × 3 filter coefficients selected by a filter coefficient α table unit 504;

FIG. 8 is a diagram showing a 3 × 3 filter coefficient multiplied by a filter coefficient indicating the priority of gradation / resolution.

FIG. 9 is a diagram illustrating an example of a highlight filter characteristic table.

FIG. 10 is a diagram illustrating an example of an intermediate luminance filter characteristic table.

FIG. 11 is a diagram illustrating an example of a shadow filter characteristic table.

FIG. 12 is a diagram illustrating an example of a luminance direction interpolation coefficient table.

FIG. 13 is a diagram illustrating a relationship between four one-dimensional tables and a two-dimensional filter coefficient α table.

FIG. 14 is a flowchart when the image processing system is implemented by software.

FIG. 15 is a detailed flowchart showing setting of a filter coefficient α table shown in FIG. 14 (S1401).

FIG. 16 is a detailed flowchart showing the gradation / resolution information control processing (S1403) shown in FIG.

FIG. 17 is a diagram illustrating a system configuration according to a third embodiment.

FIG. 18 is a block diagram illustrating a configuration of an image processing device according to a third embodiment.

FIG. 19 is a diagram illustrating an example of a highlight filter characteristic table according to the third embodiment.

FIG. 20 is a diagram illustrating an example of a shadow filter characteristic table according to the third embodiment.

[Explanation of symbols]

 301 computer 302 monitor 303 color printer 401 gradation / resolution information generation unit 402 gradation / resolution information table creation unit 403 gradation / resolution information control unit 404 color matching processing unit 405 ink color conversion processing unit 406 halftone processing unit 407 CPU 408 ROM 409 RAM 501 Luminance calculation unit 502 Spatial frequency detection unit 503 Average luminance calculation unit 504 Filter coefficient α table unit 505 3 × 3 basic filter table unit 506 3 × 3 filter operation unit 507 Highlight filter characteristic table unit 508 Intermediate luminance filter Characteristic table section 509 Shadow filter characteristic table section 510 Luminance direction interpolation coefficient table section 511 Filter coefficient α table calculation section

Continued on front page F term (reference) 5B057 CA01 CA08 CA16 CB01 CB08 CB16 CE06 CE11 CH09 5C077 LL19 MP01 MP08 NN02 PP01 PP32 PP33 PP48 PQ12 RR06 TT02 5C079 HB01 HB03 HB12 KA15 LA02 LA14 LA31 LA33 MA11 NA05

Claims (16)

[Claims] 1. A generating means for generating information indicating the priority of gradation information and resolution information for each pixel based on local characteristics of N-bit input image data; and gradation information and resolution information for each pixel. Redistribution means for redistributing resolution information to gradation information based on the information indicating the priority of the conversion, and converting the bit size of the pixel data into M (M> N) bits based on the redistributed gradation information And an image processing apparatus. 2. The image processing apparatus according to claim 1, wherein the generation unit includes: a detection unit configured to detect a spatial frequency characteristic for each pixel from local characteristics; and a calculation unit configured to calculate a luminance for each pixel from the local characteristics. A method for generating, from a frequency and calculated luminance, information indicating priority of gradation information and resolution information for each pixel according to a local spatial frequency and luminance using a two-dimensional table. 2. The image processing device according to 1. 3. The two-dimensional table includes a one-dimensional table defining characteristics of highlight, a one-dimensional table defining characteristics of intermediate luminance, a one-dimensional table defining characteristics of shadow, The image processing apparatus according to claim 2, wherein the image processing apparatus is created using a one-dimensional table that defines an interpolation coefficient in a luminance direction. 4. The redistribution means is constituted by an L × L low-pass filter, and controls a ratio between the target pixel and peripheral pixels based on information indicating priority of gradation information and resolution information. The image processing device according to claim 1. 5. The method according to claim 1, wherein the redistribution means distributes resolution information only to the highlight area and the shadow area to the gradation information without changing the characteristic of the intermediate luminance level, thereby improving the gradation reproducibility of the reproduced image. The image processing apparatus according to claim 1, wherein: 6. A color matching unit that performs color matching using the M-bit pixel data, a color conversion unit that converts the color-matched M-bit data into a color material of a printer, and the color material. 2. The image processing apparatus according to claim 1, further comprising halftone processing means for converting the M-bit data converted into the color into a bit number printable by a printer. 7. A control means for controlling an application amount of a coloring agent or a glossing agent capable of expanding a color reproduction range of a printer based on information indicating priority of gradation information and resolution information for each pixel. The image processing apparatus according to claim 1, wherein: 8. A generation step of generating information indicating priority of gradation information and resolution information for each pixel based on local characteristics of N-bit input image data; and a gradation information and resolution information for each pixel. A redistribution step of redistributing resolution information to gradation information based on the information indicating the priority of the pixel data; And an image processing method. 9. The generating step includes a detecting step of detecting a spatial frequency characteristic for each pixel from a local characteristic, and a calculating step of calculating a luminance for each pixel from a local characteristic. A method for generating, from a frequency and calculated luminance, information indicating priority of gradation information and resolution information for each pixel according to a local spatial frequency and luminance using a two-dimensional table. 9. The image processing method according to 8. 10. The two-dimensional table includes: a one-dimensional table defining characteristics of highlight; a one-dimensional table defining characteristics of intermediate luminance; a one-dimensional table defining characteristics of shadow; The image processing method according to claim 9, wherein the image processing method is created using a one-dimensional table that defines an interpolation coefficient in a luminance direction. 11. The method according to claim 11, wherein the redistribution step uses an L × L low-pass filter to control a ratio between the target pixel and peripheral pixels based on information indicating priority of gradation information and resolution information. The image processing method according to claim 8, wherein: 12. The re-distribution step includes distributing resolution information to gradation information only in a highlight area and a shadow area without changing a characteristic of an intermediate luminance level, and improving gradation reproducibility of a reproduced image. The image processing method according to claim 8, wherein: 13. A color matching step of performing color matching using the M-bit pixel data; a color conversion step of converting the color-matched M-bit data to a color material color of a printer; The image processing method according to claim 8, further comprising: a halftone processing step of converting the M-bit data converted into the color into a bit number printable by a printer. 14. A control step of controlling a coating amount of a coloring agent or a glossing agent capable of expanding a color gamut of a printer based on information indicating priority of gradation information and resolution information for each pixel. The image processing method according to claim 8, wherein: 15. A computer-readable recording medium on which a program for an image processing method is recorded, wherein the program comprises: gradation information and resolution information for each pixel based on local characteristics of N-bit input image data. A generation step of generating information indicating the priority of the pixel; a redistribution step of redistributing resolution information to gradation information based on the gradation information of each pixel and information indicating the priority of the resolution information; and Converting the bit size of the pixel data into M (M> N) bits based on the obtained gradation information. 16. The generating step includes a detecting step of detecting a spatial frequency characteristic for each pixel from a local characteristic, and a calculating step of calculating a luminance for each pixel from a local characteristic. A method for generating, from a frequency and calculated luminance, information indicating priority of gradation information and resolution information for each pixel according to a local spatial frequency and luminance using a two-dimensional table. 16. The recording medium according to 15.