JP2001175843A - Image processing method, image processor and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce color noise without degrading the apparent resolution of even texture on an image that it is hard to find only with an edge from a luminance signal and to effectively reduce the color noise without repeating plural color noise reducing processes. SOLUTION: An edge decision part (S2) decides an edge parts on the image and a chromaticity variation decision part (S3) decides a color edge part on the image; and a color difference signal is smoothed with respect to an image signal that neither decision part decides. The smoothing process is carried out by using a result after a filter process as a new input.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus for correcting an image signal, and more particularly, to an image processing method for reducing color noise, an apparatus therefor, and a recording medium.

[0002]

2. Description of the Related Art In recent years, with the development of hard copy technology, especially full-color hard copy technology, high-fidelity images can be reproduced by using a printing technology such as an ink jet recording system and a high-resolution digital camera. is there. The color reproduction has evolved to the point that it is said that the recording material and image processing provide the same reproduction capability as silver halide photography.

However, there is a drawback that an image to be printed sometimes contains color noise due to characteristics of an image pickup device or the like in an input device. For example, CC
Noise due to dark current of D element, fixed pattern noise,
There is a disadvantage that noise or the like generated on a signal line for transmitting a color signal may be mixed in an input image.

In order to overcome this drawback, Japanese Patent Application Laid-Open No.
In JP-A-153608, an arithmetic average of a target pixel and upper and lower dye data adjacent vertically is taken, whereby
It describes that a vertical smoothing filter is applied to the dye data without deteriorating the luminance of the image.

[0005] Further, by detecting the correlation between the luminances of three consecutive pixels in the vertical direction, the dye data also has a large change in the edge portion where the luminance in the vertical direction changes greatly according to the luminance correlation. Therefore, the degree of application of the smoothing filter is reduced, and when the change in luminance is small, the degree of application of the smoothing filter is increased. The above-mentioned publication discloses a method for extending the smoothing of the dye data in the vertical direction with a simple configuration by repeating the arithmetic operation for performing the arithmetic averaging a plurality of times on the target pixel with a simple configuration.

[0006]

However, when the above-described conventional color noise elimination is applied to an image signal, an apparent resolution of a texture on an image which is difficult to be detected only by an edge from a luminance signal may be deteriorated. Further, when the chromaticity of the color noise of interest is significantly different from the chromaticity of its surroundings, there is a problem that it is necessary to repeat the color noise removal processing for the pixel of interest a plurality of times.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an image processing method, apparatus, and storage medium capable of realizing high-level color noise reduction without deteriorating the apparent resolution of a color signal. .

[0008]

According to the present invention, color image data composed of a signal indicating a brightness and a signal indicating a tint is input, and while the signal indicating the brightness is held,
The smoothing process is performed on the signal indicating the color.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS (First Embodiment) FIG. 1 shows an image processing apparatus 100 according to a first embodiment of the present invention.
FIG.

The image processing apparatus 100 is composed of a host computer, and a printer 106 such as an ink jet printer and a monitor 105 are connected to each other.

An image processing apparatus 100 includes application software 101 such as a word processor, a spreadsheet, and an Internet browser, and an OS (Operating System) 102.
And a printer driver 103 that processes various drawing commands (image drawing command, text drawing command, graphics drawing command) indicating an output image issued by the application to the OS 102 and creates print data.
And a monitor driver 104 that processes various drawing commands issued by the application and displays the result on the monitor 106 as software.

The image processing apparatus 100 includes a central processing unit CPU 108 and a hard disk driver HD 107 as various hardware on which the above software can operate.
, A random access memory 109, a read only memory ROM 110, and the like.

The image processing apparatus 100 uses, for example, Microsoft Windows 95 as an OS and installs an arbitrary printable application on an IBM AT compatible personal computer which is widely used. The monitor 106 and the printer 106 are connected to this.

In the image processing apparatus 100, based on a display image displayed on a monitor, text data classified into text such as characters created by the application 101,
Graphics data classified as graphics such as graphics, image image data classified as natural images, and the like are converted into output image data.

When printing output image data,
The application 101 issues a print output request to the OS 102. The application 101 issues a graphics rendering command to the OS 102 for the graphics data portion, and issues a rendering command group indicating an output image composed of the image rendering command to the OS 102 for the image data portion.

The OS 102 receives an output request from an application, and receives a printer driver 1 corresponding to the output printer.
03, a drawing command group is issued. Printer driver 103
Processes the print request and the drawing command group input from the OS 102, creates output image data printable by the printer 106, and transfers it to the printer 106.

When the printer 106 is a raster printer, the printer driver 103 sequentially performs image correction processing in response to a drawing command from the OS 102, and sequentially executes RG
After rasterizing into a 24-bit page memory and rasterizing all drawing commands, the contents of the RGB 24-bit page memory are converted into a data format printable by the printer 106, for example, CMYK data.
Transfer to 6.

Next, a processing operation performed by the printer driver 103 in the above embodiment will be described.

FIG. 2 is a diagram showing the printer driver 103 in the above embodiment.

The printer driver 103 has an image correction processing unit 120 and a printer correction processing unit 121.

The image correction processing unit 120 performs an image correction process on the color information included in the drawing command group input from the OS 102. In this image correction process, a color noise reduction process is performed based on the RGB color information.

The printer correction processing unit 121 first rasterizes a drawing command based on the color information subjected to the image correction processing, and generates a raster image on an RGB 24-bit page memory. Then, CMYK data depending on the color reproducibility of the printer is generated for each pixel, and the printer 10
Transfer to 6.

The outline of the color noise reduction processing performed by the image correction processing section 120 will be described.

(Color Noise Reduction Processing Unit) FIG. 3 is a schematic diagram for explaining the outline of the processing of the image correction processing unit 120.

At B1, the input RGB signals are
The luminance signal Y and the color difference signal CrCb are converted. Then, the signal smoothing units B2 and B3 perform a smoothing process on the color difference signal, and perform a reverse conversion to an RGB signal at B4.

In this embodiment, the color noise is reduced by smoothing the rapid change of the color difference signal while maintaining the luminance signal.

Next, the operation of reducing the color noise by smoothing the rapid change of the color difference signal while holding the luminance signal will be described.

In the color noise reduction processing section, the luminance signal Y
While maintaining (i, j), the color difference signals Cr (i, j),
By using the low-pass filter shown in FIG. 5 for Cb (i, j), as shown in the following equation (5),
Smooth sudden changes in color difference signals.

FIG. 5 is a diagram showing a weight configuration of the low-pass filter.

As shown in FIG. 5, the target pixel (i,
By configuring the filter so as to surround j), stable color noise reduction processing can be performed regardless of the direction of the input image. Note that the target pixel is the number of pixels surrounded by a circle in the figure.

[0031]

(Equation 1)

Here, m (•, •) represents a filter, and f (•, •) represents a signal. Here, instead of the Cr (i, j) and Cb (i, j) signals,
f (•).

When the filter processing shown in Expression (5) is used as it is, the filter processing cannot be performed on the peripheral portion of the image. In this case, Japanese Patent Application Hei 11-
As shown in Japanese Patent No. 189637, an appropriate peripheral processing may be performed.

In the above embodiment, NTSC Y, Cr, C
Although the b signal is used, instead of the luminance signal, for example, a G signal of an RGB signal is used, and Cr ′ =
R / (R + G + B), Cb '= B / (R + G + B) or the like may be used.

Even if the above color noise reduction processing is performed using a coordinate system such as L ^* a ^* b ^* and Yxy, the same effect as described above can be obtained. For cylindrical coordinate systems such as L ^* c ^* h ^* and HLS, it is conceivable to perform the same processing as described above. In this case, after performing processing for converting coordinate values in the cylindrical coordinate system to rectangular coordinates, You may make it smooth.

If it is sufficient to correct only the color distortion, the change in the hue angle may be smoothed. Similarly, smoothing the saturation has the same effect as described above.

[0037]

(Equation 2)

In another embodiment, after executing equation (5), as shown in equation (6), the value after smoothing the color difference signal is fed back to the signal side of the original image. By doing so, the smoothing effect can be further enhanced.

When performing the above feedback processing, FIG.
As shown in (2), a filter to which a higher weight is assigned for a processed signal value than for an unprocessed signal value may be used. By doing so, the smoothing effect of the color difference signal can be further enhanced.

Further, by configuring the weights of the filters used in FIG. 6 and the like so that the denominator is a power of 2, it is possible to use a shift operation mechanism of the register, and it is possible to perform high-speed processing. Become.

The filter is not limited to a filter having a size of 5 × 5 or a target in the vertical and horizontal directions, and the same color noise reduction effect can be obtained as long as the filter has a low-pass characteristic. Of course, a median filter may be used, and the same effect as described above can be obtained.

Further, the filter size may be appropriately changed according to the image resolution. By changing the filter size, a stable processing result can be obtained regardless of the image resolution.

In the real space, real time domain, and spatial frequency domain, the same effect can be obtained by performing processing for reducing high frequency components on signals other than the luminance signal Y.

FIG. 4 is a flowchart showing the operation of the color noise reduction processing.

A color noise reduction process is performed on the image data portion of the same image indicated by the image drawing command. Therefore, for example, when a graphics image and an image image are included in the same output image, the image image portion is extracted according to the result of analyzing the drawing command, and color noise reduction processing is performed.

With the color noise reduction processing alone, the apparent resolution may be degraded at the edge portion of the luminance or at the color edge portion where a sudden change in chromaticity is perceived. Therefore, in the present embodiment, an edge determination unit, a color edge determination unit, an edge emphasis unit, and the like are added to prevent deterioration in the apparent resolution of edges and color edges.

The color noise reduction processing performed on the extracted image data will be described in detail.

(Edge Calculation Unit) The edge calculation unit calculates an edge of the luminance signal Y using, for example, a Laplacian filter or the like, and holds the calculated value D_Y (S1).

The calculated value D_Y can be used in both the edge determination unit and the edge enhancement unit, which are the subsequent steps. In addition, when edge enhancement is not performed, or when a high-speed unit dedicated to edge enhancement is available,
The obtained value D_Y may be discarded at the same time as the end of the edge determination.

In the above embodiment, a Laplacian filter is used. However, a pass component of a high-pass filter in the spatial frequency domain may be used for edge calculation. Alternatively, the same effect as described above can be obtained.

(Edge Judgment Unit) The edge judgment unit judges the edge by comparing the value D_Y held by the edge calculation unit with a threshold value TH_Edge used for edge judgment (S2).

The threshold value TH_Edge may be set for each processing object, for example, by analyzing a histogram of an input image. In this case, for example, a frame memory for storing the differential value of the luminance signal of the original image is prepared, a histogram is again taken for the frame memory storing the differential value, and the obtained histogram is subjected to, for example, a discriminant analysis method. Analysis may be performed using a technique, and pixel values may be clustered, and an appropriate threshold may be obtained each time. A histogram calculation / analysis unit is required.

As a result of the judgment by the edge judgment unit, the target pixel f
When it is determined that (i, j) is an edge, the process proceeds to the chromaticity change determination unit (S3). In addition, when it is not determined that an edge is present, if the deterioration of the apparent resolution in the edge emphasizing unit (S5) does not matter, the edge determination step may be omitted.

(Edge Emphasis Unit) The edge emphasis unit performs edge emphasis by adding a luminance signal value Y (i, j) to the held value D_Y (S5).

That is, Y ′ (i, j) = Y (i, j) + D_Y (Equation 1) is performed.

By performing edge enhancement after the color noise reduction processing or together with the color noise reduction processing, edge enhancement can be performed without enhancing color noise.

Here, the processing is speeded up and simplified by performing edge emphasis using the data obtained for the edge determination. However, at another stage in the flowchart shown in FIG. An emphasis process may be performed.

If edge enhancement has already been performed on the input device side, edge enhancement need not be performed at this stage.

The edge region of one or more pixels including the pixel of interest may be passed without processing the original image data without performing edge enhancement. In this case, it is possible to faithfully reproduce the original image in the image area other than the color noise area.

(Chromaticity change judging section) In the chromaticity change judging section,
A "color edge" (a portion where the chromaticity changes rapidly) that cannot be detected from the change in the luminance signal Y is detected (S3).

D_col_CrL (i, j) = | {Cr (i-2, j-1) + Cr (i-1, j-1) + Cr (i, j-1)}-{Cr (i + 2, j + 1) + Cr (I + 1, j + 1) + Cr (i, j + 1)｝ | Equation (2) D_col_CrR (i, j) = | {Cr (i + 2, j + 1) + Cr (i + 1, j + 1) + Cr (i, j + 1)}-｛ Cr (i−2, j−1) + Cr (i−1, j−1) + Cr (i, j−1)｝ | Equation (3) Similarly to the above, the Cb component is also obtained. Then, the calculated value D_col (i, j) is compared with a threshold value TH_col for determining chromaticity change, and chromaticity change determination is performed.

In the above embodiment, the threshold value TH_col is a fixed value. However, a feature amount such as a histogram of an input image may be calculated, and a chromaticity change determination may be performed based on the calculated feature amount. . In addition, a similar effect can be obtained by configuring the chromaticity change value D_col (i, j) using the differential value of the color difference signal. Here, as a method of automatically setting the threshold value TH_col, a method such as the discriminant analysis method described in the “edge determination unit” may be appropriately used.

In the chromaticity change determination processing in the above embodiment, the color noise portion may be determined as a color edge depending on the value of the threshold value TH_col. In such a case, a bandpass filter configured to pass only the color edge in consideration of the frequency characteristics of the color edge may be used instead of the value D_col (i, j) used for the determination. .

It is to be noted that another method for detecting a rapid change in chromaticity from only the color difference signal regardless of the change in luminance Y may be used. For the edge portion and the color edge portion, the color noise reduction process is not performed in order to prevent the apparent resolution from deteriorating, and the process proceeds to the next pixel (S6). Here, when it is determined that the edge portion or the color edge portion is present, the pixel may be skipped by several pixels in order to maintain the consistency of the image around the edge portion. For a pixel that is not an edge portion or a color edge portion, color noise reduction processing is performed in S4. These processes are sequentially performed on a portion extracted as an image image.

(Second Embodiment) Here, in order to avoid complication of description, in the description of the second embodiment, only parts different from those of the first embodiment will be partially described.

(Edge Judgment Unit / Chromaticity Change Judgment Unit) In the first embodiment, the edge judgment unit and the chromaticity change judgment unit process the input image data for those judged to be edges and color edges, respectively. Is not added.

However, in the processing after the edge determination and the processing after the chromaticity change determination, the connecting portion between the edge portion and the non-edge portion may be too conspicuous.

In such a case, the chromaticity data Col (i, j) (= Cr (i, j), Cb
(I, j)), E (i, j) = D_Y (i, j) * H (D_Y (i, j) -TH_Edge) / TH_Edge... Equation (7) i, j) are defined. Using this, Col (i, j) = E (i, j) * Col (i, j) + (1−E (i, j)) * Low (Col (i, j)) Equation By calculating the weighted average of the target chromaticity data and the chromaticity data after passing through the low-pass filter as in (8), it is possible to make the connecting portion between the edge portion and the non-edge portion inconspicuous. it can.

Here, H (•) is a step function of Heaviside, and Low (•) is a low-pass filter.

(Other Judgment Section, High Saturation Judgment Section) Color noise is often conspicuous in a low saturation area. Therefore,
Saturation S (i, j) (= sqrt (Crｒ2 +
Cb ＾ 2)) is calculated, and when the saturation S (i, j) exceeds, for example, TH_Saturation, the color noise reduction processing is not performed. By doing so, it is possible to realize faithful reproduction of a high-saturation portion and speed-up of processing.

The color noise in the achromatic region may cause the achromatic region to appear partially colored. Therefore, if the target pixel is an achromatic color, the color noise reduction processing is not performed. By doing so, it is possible to faithfully reproduce an achromatic portion and to speed up processing.

(Modification) In the above embodiment, the color noise reduction processing is performed uniformly irrespective of whether or not the target pixel is color noise.

However, the effect can be further enhanced by performing the processing of detecting the color noise or the degree of the color noise, and performing the color noise reduction processing in accordance with the detected color noise portion or the degree of the color noise. .

As a method for detecting color noise, for example, there is a method using a differential value on a chromaticity plane. A mode for reducing the color noise based on the designation of the color noise area by the user's manual may be provided.

If the ratio of the color noise in the processing target area is defined as the color noise level, the color noise level Cn (i, j) is
It can be obtained by the following equation.

Cn (i, j) = | (Col (i, j) −med (Col (i, j))) | / (| med (Col (i, j)) |) (9) Here, med (•) is an intermediate value of the chromaticity of the target pixel and eight pixels adjacent to the target pixel.

For data having a high degree of color noise Cn (i, j), the above-described color noise reduction processing is performed by using a filter in which pixels far from the target pixel as shown in FIG. A higher color noise reduction effect can be obtained.

Here, if the target area for calculating the intermediate value med (•) is an area including the pixel of interest,
Regardless of its shape and size. Furthermore, the intermediate value med
Instead of using (•), an average value may be used, and in this case, the same effect as described above can be obtained.

(Third Embodiment) Here, in order to avoid complication of description, the same reference numerals are given to the same processing units as in the first embodiment, and description thereof will be omitted.

FIG. 8 is a flowchart showing the operation of the color noise reduction processing of this embodiment.

(Highlight Judgment Unit) In a hard copy device such as an ink jet printer, white
The system uses paper white instead. For this reason, the white portion (R = G = B = 255) is paper white, but the non-white portion is, for example, dot-printed by an ink-jet printer. May be felt discontinuously.

FIG. 14 is a schematic diagram showing image data that undergoes filter processing with different colors for each of the divided areas during the image data division processing, and an image division method.

By the way, as shown in FIG. 14, a white block (FIG. 14-11) and a block containing a white block but partially non-white texture (FIG. 14-12)
Is present, the color noise reduction process
When the target pixel and the surrounding pixels are smoothed, the color may slightly differ between the white block and the non-white block. The white block is paper white, and the non-white block may be dotted.

Therefore, the highlight judging section judges the point at which the paper should be white (S11), and does not perform the color noise reduction processing on the determined point at which the paper should be white (S6). . Note that the highlight determination method here is (R ≧ 250) AND (G ≧ 250) AND (B ≧ B
250) or a method of determining a highlight such as Y ≧ 250 may be used as appropriate.

After performing the color noise reduction processing, it is sometimes desired to perform image processing such as brightness correction processing using the brightness correction curve shown in FIG. In this case as well, the pixel originally having the pixel value of 235 is changed to the pixel value of 234 or 236 by the smoothing process in the color noise reduction process, as described above. And a band uneven area where dots are formed.

In such a case, a highlight point HL is determined from the brightness correction curve determined above (S11), and the pixel having a pixel value near the determined highlight point HL is subjected to the color noise reduction processing. Not performed (S
6).

In a printer such as a sublimation type printer capable of sufficiently obtaining gradations, the band unevenness is often not so noticeable. In such a case, the highlight determination process may not be performed.

With the color noise reduction processing alone, the apparent resolution of the edge portion of the luminance and the color edge portion where a sharp chromaticity change is perceived despite a small change in the luminance may be deteriorated. Therefore, in this embodiment, an edge determination unit, a color edge determination unit, an edge enhancement unit,
This prevents deterioration of the visual resolution of the color edge.

(Scene switching determining unit: color difference determining unit between rows) In the above embodiment, the color noise reduction processing is performed by using the 5 × 5 filter shown in FIG.

In this configuration, the image data sent as numbers 3 and 8 in FIG. 12 are also subjected to the filter processing in the same manner as the other image processing unit blocks. , The smoothing is performed using the discontinuous ground brown and blue sky in the original image data (the thick broken line portion in FIG. 12), and the color of the image after the filter processing is performed. There is room for improvement that changes.

Therefore, in the above embodiment, the average color difference between the line to be processed and the line one line above the line to be processed is determined by the color difference threshold value Th_ColDi in the color difference determining section between the lines.
If it is not ff # Line or less, it is considered that the input image data to the image processing module is discontinuous, and the input image data is detected as a discontinuity point (S12).

In the present embodiment, the type of filter is switched based on the line detected as a discontinuous point and the positional relationship between the target image data.

FIG. 9 is a diagram showing a weight configuration of the low-pass filter. FIG. 9A is for three-row processing, and FIG.
FIG. 9C shows a filter for row processing, and FIG. 9C shows a filter for one-row processing.

FIG. 10 is a state transition diagram showing a processing sequence when a filter for processing an image is switched according to a position in an image to be processed, which includes a scene switching determination unit.

FIG. 11 is a schematic diagram showing how to switch the filters when the filters used in the color noise reduction processing are switched according to the position in the image to be processed.

In the color noise reduction processing, as shown in FIG. 11, when the first line of the input image is processed, only the first line of the image is used and the color difference signal is smoothed by the filter shown in FIG. 9C. (FIG. 11-L1, FIG. 10-P1), and when processing the second line of the input image, the second line of the image and its first
The color difference signal is smoothed by the filter shown in FIG. 9B using the first row above (FIG. 11-L2, FIG. 10-P).
2) When processing the third line of the input image, the filter shown in FIG. 9A is used by using the third line of the image, the second line above the third line, and the first line above two. (FIG. 11-L3, FIG. 1
0-P3) Perform smoothing (S13).

That is, when the discontinuity point of the input image data is detected by the above-mentioned color difference judgment section between the rows, the processing shown in FIG.
1 and T31, the filter processing area is
An operation (memory refresh operation) of switching from the three-row process of 0-P3 or the two-row process of FIG. 10-P2 to the one-row process of FIG. 10-P1 is performed.

By performing filter processing using such a filter configuration, for example, as shown in FIG. 12, one image data is divided by an application,
Even when the image is input to the image processing module, appropriate filter processing can be performed. Here, the number 1 in FIG.
Numerals 10 to 10 indicate ranges of image data to be divided into image processing modules and input. The arrow in FIG.
The range of image data used to smooth the line of interest indicated by ○ is shown.

Further, by performing a filtering process using such a filter configuration, an output can be obtained every time image data is input. In response to the input of image data, the output of the processed image data is Filter processing with no delay can be performed.

In determining the above average color difference,
The average color difference does not necessarily need to be an accurate average color difference. For example, the average color difference obtained for 10 pixels of the target line on the image may be appropriately sampled and used. Further, the color difference may be obtained using only the R component of the RGB data and only the Y component of the YCrCb data, for example.

(Fourth Embodiment) In order to realize the functions of the above embodiments, the program code itself for realizing the functions of the embodiment is installed in an apparatus or system connected to various devices for operating various devices. A means for supplying the program code to the computer, for example, a storage medium storing the program code is also an embodiment of the present invention.

As the storage medium for storing the program code, for example, a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, magnetic tape, nonvolatile memory card, ROM, etc. can be used.

The functions of the above-described embodiments are not only realized by the computer executing the supplied program code, but the program code is executed by an OS (Operating System) running on the computer or another program. Such a program code is an 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
After being stored in the memory provided in the function expansion board of the computer or the function expansion unit connected to the computer, the CPU or the like provided in the function expansion board or the function storage unit executes the actual processing based on the instruction of the program code. The embodiment of the present invention also includes a case where the functions of the above-described embodiment are realized by performing a part or all of the processes. Further, the above embodiments may be combined.

That is, in the above-described embodiment, the input procedure for inputting color image data composed of the signal indicating the brightness and the signal indicating the tint, and the tinting while holding the signal indicating the brightness are performed. 2 is an example of a computer-readable recording medium on which a program for causing a computer to execute a smoothing process procedure for performing a smoothing process on a signal indicating the following is recorded.

In the above embodiment, the input procedure for inputting a drawing command indicating an output color image, the detection procedure for detecting an image data section based on the drawing command, and the 7 is an example of a computer-readable recording medium on which a program for causing a computer to execute a color noise reduction processing procedure for performing a noise reduction processing is recorded.

Further, the above embodiment is an image processing method for performing a filtering process on color image data, and a detection procedure for detecting a scene switching portion in accordance with the color image data and peripheral color image data. And a filter size switching procedure for switching a filter size in accordance with a result of the above detection.

[0108]

According to the present invention, it is possible to achieve a high level of color noise reduction without deteriorating the apparent resolution of a color signal.

[Brief description of the drawings]

FIG. 1 is an image processing apparatus 10 according to a first embodiment of the present invention.
It is a figure which shows the outline of 0.

FIG. 2 is a diagram showing a printer driver 103 in the embodiment.

FIG. 3 is a block diagram illustrating an image correction processing unit 120 according to the embodiment.

FIG. 4 is a flowchart illustrating an operation of a color noise reduction process performed by an image correction processing unit 120 in the embodiment.

FIG. 5 is a diagram showing a weight configuration of a low-pass filter.

FIG. 6 is a diagram showing a filter to which a higher weight is assigned than an unprocessed signal value;

FIG. 7 is a diagram illustrating a filter in which a pixel far from a target pixel is weighted with a high weight;

FIG. 8 is a flowchart illustrating an operation of a color noise reduction process to which edge determination and the like are added.

FIG. 9 is a diagram showing a weight configuration of a low-pass filter.

FIG. 10 is a state transition diagram showing a processing sequence when a filter for processing an image is switched according to a position in an image to be processed, which includes a scene switching determination unit.

FIG. 11 is a schematic diagram illustrating how to switch filters when a filter for processing an image is switched according to a position in an image to be processed.

FIG. 12 is a schematic diagram showing a method of dividing image data when dividing and processing image data.

FIG. 13 is a diagram of a brightness correction curve when performing brightness correction.

FIG. 14 is a diagram illustrating image data that is subjected to filter processing with different colors for each divided area during the division processing of the image data,
It is a schematic diagram which shows the division method of an image.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 100 ... Image processing apparatus, 101 ... Application software, 102 ... OS, 103 ... Printer driver, 104 ... Monitor driver, 105 ... Monitor, 106 ... Printer, 107 ... Hard disk driver, 120 ... Image correction processing unit, 121 ... Printer Correction processing unit.

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Makoto Torigoe 3-30-2 Shimomaruko, Ota-ku, Tokyo Inside Canon Inc. (72) Inventor Manabu Yamazoe 3-30-2 Shimomaruko, Ota-ku, Tokyo Canon F term (reference) 5B057 CA01 CB01 CE02 CE03 CE05 CE06 CE18 DC16 5C077 LL02 LL19 MP08 PP02 PP03 PP32 PP33 5C079 HB01 HB02 HB12 LA06 LA14 NA02

Claims (21)

[Claims] 1. An input step of inputting color image data composed of a signal indicating brightness and a signal indicating tint; and holding the signal indicating brightness while maintaining the signal indicating tint. Performing a smoothing process by performing a smoothing process. 2. The method according to claim 1, wherein the input step includes a step of converting color image data composed of a plurality of color component signals into a signal indicating the brightness and a signal indicating the tint. An image processing method comprising: 3. The method according to claim 1, wherein, based on the signal indicating the brightness, it is determined whether or not the color image data having the signal indicating the brightness is an edge portion. Not performing the smoothing process if it is determined that the image is a part. 4. The image processing method according to claim 3, wherein when the color image data is determined to be an edge portion, an enhancement process is performed on the signal indicating the brightness. 5. The color image data according to claim 1, wherein the color image data having the color signal is a color change portion based on the color signal. Not performing the smoothing process when is determined to be a color change portion. 6. The method according to claim 1, further comprising: determining whether the color image data is a highlight portion; and performing the smoothing process when the color image data is determined to be a highlight portion. An image processing method. 7. The image processing method according to claim 1, wherein the smoothing process is a process performed using a filter that is symmetric in a vertical and horizontal direction with respect to a target pixel. 8. The smoothing process according to claim 1, wherein the smoothing process is a filtering process using a peripheral pixel of the input color image data as a target pixel.
An image processing method used for smoothing other color image data. 9. The method according to claim 8, wherein the smoothing process is a process using a filter having a high weight for a pixel area to which the smoothing process is performed before the pixel of interest. An image processing method characterized by being processed. 10. An inputting step of inputting a drawing command indicating an output color image; a detecting step of detecting an image data portion based on the drawing command; and performing a color noise reduction process on the image data portion. A color noise reduction processing step. 11. The color noise reduction processing according to claim 10, wherein the color noise reduction processing holds the signal indicating the brightness for the color image data composed of the signal indicating the brightness and the signal indicating the tint. And a smoothing process performed on the signal indicating the color. 12. The image processing method according to claim 10, wherein the color noise reduction processing is not performed when a graphic image data portion is detected based on the drawing command. 13. An image processing method for performing a filtering process on color image data, comprising: a detecting step of detecting a scene switching portion according to the color image data and peripheral color image data; A filter size switching step of switching a filter size according to a result. 14. The image processing method according to claim 13, wherein the filter used in the filter processing is a filter that refers to a line of interest to which the pixel of interest belongs and a line preceding the line of interest. . 15. A drawing command group input step of inputting a drawing command group indicating an output image; an image data generating step of generating output image data indicating an output image based on the drawing command group; An image processing method, comprising: a dividing step of dividing the same image by a plurality of drawing commands; and a divided image inputting step of inputting the plurality of divided images. 16. An input means for inputting color image data composed of a signal indicating brightness and a signal indicating tint; and holding the signal indicating brightness while responding to the signal indicating tint. An image processing apparatus comprising: a smoothing processing unit for performing a smoothing process by using an image forming unit for forming an image based on the signal indicating the brightness and the signal indicating the color subjected to the smoothing process; . 17. An input unit for inputting a drawing command indicating an output color image; a detecting unit for detecting an image data portion based on the drawing command; and performing a color noise reduction process on the image data portion. An image processing apparatus comprising: a color noise reduction processing unit; and an image forming unit. 18. An image processing apparatus for performing a filtering process on color image data, comprising: detecting means for detecting a scene switching portion according to the color image data and peripheral color image data; An image processing apparatus comprising: a filter size switching unit that switches a filter size according to a result; and an image forming unit. 19. An input procedure for inputting color image data composed of a signal indicating brightness and a signal indicating tint; and holding the signal indicating brightness while maintaining the signal indicating tint. And a computer-readable recording medium storing a program for causing a computer to execute a smoothing process procedure for performing a smoothing process. 20. An input procedure for inputting a rendering command indicating an output color image; a detection procedure for detecting an image data portion based on the rendering command; and performing a color noise reduction process on the image data portion. A computer-readable recording medium which records a program for causing a computer to execute a color noise reduction processing procedure. 21. An image processing method for performing a filtering process on color image data, comprising: a detection procedure for detecting a scene switching portion according to the color image data and peripheral color image data; Depending on the result,
And a computer-readable recording medium storing a program for causing a computer to execute a filter size switching procedure for switching a filter size.