JP2000013622A - Image processing method, device and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain a satisfactory output image by analyzing a relation among plural object images, grouping the object images based on the analyzed result and setting the same color processing condition to object images pertaining to the same group. SOLUTION: Image data showing plural object images are inputted, the relation among the plural object images is analyzed, the plural object images are grouped based on the analyzed result and the same color processing condition is set to the plural object images pertaining to the same group. In this system, for instance, a printer 105 such as an ink jet printer and a monitor 106 are connected to a host computer 100. The computer 100 has application software 101, a printer driver 103, a monitor driver 104 and color matching module 111 as software.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing method, apparatus, and recording medium for performing image processing.

[0002]

2. Description of the Related Art When an output image based on image data is satisfactorily output by a printer or a display, color correction processing, color conversion processing, It is necessary to perform color processing such as binarization processing. Generally, in printing an image created by a computer application and displaying the image on a display, a device driver or device converts a drawing instruction group from the application into an image of the drawing instruction, creates image data of the entire page, and prints and displays the image data.

For example, a drawing command group that constitutes a document is issued to a vice driver, for example, an image drawing command for a photographic image portion, a text drawing command for a text portion, and a graphics drawing command for a graphics portion. Color processing suitable for the object is performed for each type, and the object is converted into an image that can be output by an output device.

At this time, the color matching processing is switched to "color processing giving priority to vividness" for the graphics part, "colorimetric matching" for the text part, and "color processing giving priority to tint" for the photograph part. Good output can be obtained for all objects on the entire page.

In recent years, depending on the system or application, a "source color space" is specified for these objects, and a device driver can obtain higher quality output using the specified contents. ing. For example, when a scanner input image is pasted on a document, when a color profile describing the device characteristics of the scanner is specified in an image drawing command of the image, or when color calibration or the like is performed on a display, the editor A color profile describing the characteristics of the monitor used to reproduce the apparent color of the monitor can be specified. These color profiles are, for example, ICC profiles. As a system that can use these color profiles, ICM, App of Microsoft Windows
leSync's ColorSync is known.

In the case of a photographic image, if the original image itself is inferior, a beautiful high-quality output cannot be naturally obtained. For example, if the exposure of an image captured by a digital camera that has become widespread in recent years is also inappropriate, image correction processing such as non-linear color balance processing for correcting exposure of a document image is performed using image retouching software.

[0007]

In a relatively high-grade application for optimizing the memory use efficiency and processing speed, a large image is internally divided as shown in FIG. May be processed. For example, it is well known that this processing is performed by Adobe PhotoShop v4.0.

Therefore, if a process for obtaining a processing condition in accordance with the color distribution of a document image, such as a process for correcting the exposure of a document image, is performed for each object image, the following problem occurs.

Different color processing conditions are originally set for each part internally divided by an application with respect to one image, and color tone discontinuity may occur at the boundary of each part in an output image. is there.

[0010] The first invention of the present application has been made in view of the above-mentioned point, and a good output image can be obtained by setting the same color processing condition for one image. The purpose is to do.

When automatically setting image correction processing such as non-linear color balance processing for correcting exposure of a document image, it is necessary to analyze the color distribution of the document image. Conventionally, in order to speed up processing, image data has been sampled under a fixed sampling condition regardless of image conditions. However, if a conventional method is used in a recent system in which images of various image data sizes are input, the number of image data samples is not enough to set an optimal processing condition, or the number of image data samples is reduced. There is a problem that it takes too much time to process. That is, the conventional method cannot set the optimum processing conditions efficiently.

A second object of the present invention is to set a sampling condition according to an image data size so that a color processing condition can be efficiently obtained.

[0013]

According to a first aspect of the present invention, there is provided an image processing method for performing color processing according to an object image, comprising the steps of: inputting image data representing a plurality of object images; Is analyzed, a plurality of object images are grouped based on the analysis result, and the same color processing condition is set for the plurality of object images belonging to the same group.

According to a second aspect of the present invention, image data representing an input image is input, a sampling processing condition is set according to the image data size of the input image, and the input image data is input under the set sampling condition. And processing conditions are obtained by analyzing the sampled image data.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS (First Embodiment) An embodiment of the present invention according to the present invention will be described below in detail with reference to the drawings. FIG. 1 shows a schematic example of a system according to the present embodiment.

The host computer 100 includes a printer 105 such as an ink jet printer and a monitor 1.
06 is connected. The host computer 100
Processes and prints application software 101 such as a word processor, spreadsheet, Internet browser, etc., and various drawing commands (image drawing command, text drawing command, graphics drawing command) indicating an output image issued to the OS 102 by the application. The software includes a printer driver 103 for creating data, a monitor driver 104 for processing various drawing commands issued by the application and displaying it on the monitor 106, and a color matching module 111 for performing color matching processing in response to a request from the application. Have as wear.

The host computer 100 includes a central processing unit CPU 108 and a hard disk driver HD 10 as various hardware on which the software can operate.
7, a random access memory RAM 109, a read only memory ROM 110, and the like.

In the embodiment shown in FIG. 1, for example, Microsoft Windows 95 is used as an OS on a commonly used IBM AT compatible personal computer, an arbitrary printable application is installed, and a monitor and a printer are connected. This embodiment is considered as one embodiment.

In the host computer 100, based on the display image displayed on the monitor, the application 10
In step 1, output image data is created using text data classified as text such as characters, graphics data classified as graphics such as figures, image image data classified as natural images, and the like. When printing out the output image data, the application 101 issues a print output request to the OS 102, and the graphics data portion is a graphics drawing command, and the image image data portion is a drawing command indicating an output image composed of an image drawing command. The group is issued to the OS 102. OS102
Receives an output request from the application and issues a rendering command group to the printer driver 103 corresponding to the output printer. The printer driver 103 processes a print request and a drawing command group input from the OS 102, creates print data printable by the printer 105, and transfers the print data to the printer 105. When the printer 105 is a raster printer, the printer driver 103 sequentially sends drawing commands from the OS to the RGB2 printer.
After rasterizing into a 4-bit page memory and rasterizing all drawing commands, the data in the RGB 24-bit page memory can be printed by the printer 105 in a data format, for example,
Convert to CMYK data and transfer to printer.

Next, the printing process performed by the printer driver 103 will be described.

The printing process performed by the printer driver 103 is roughly classified into the following five processes.

(1) Identification Processing By determining the type of an instruction for drawing an object image input from the OS 102, it is determined whether the object indicated by the drawing instruction is a photograph image portion or a text portion graphics portion. .

(2) Image Correction Processing The image correction processing corrects a color balance that has been destroyed due to the influence of photographing conditions and the like.

A luminance histogram is created for the photographic image, and a nonlinear color balance correction condition is obtained. Then, the color balance, contrast, and saturation of the photographic image are satisfactorily corrected by performing nonlinear color balance correction on the photographic image.

Hereinafter, an image correction processing method will be described with reference to FIGS.

In the image correction processing of this embodiment, color balance correction, contrast correction, and saturation correction processing are performed.

(Color Balance Correction) A highlight point and a shadow point are determined from an image. In that case,
For example, a cumulative frequency histogram is created for a lightness signal obtained by weighting and adding each of the color signals R, G, and B of the input signal,
In the cumulative frequency histogram, an upper limit value of a brightness signal corresponding to a predetermined cumulative frequency set in advance is determined as a highlight point, and a lower limit value is determined as a shadow point.

The color difference signals (C1, C2) C1 = RY-C2 = BY of the pixels having the brightness of the highlight point and the shadow point of the image are stored. Then, the average values are respectively used as the color difference amounts (C1 (HL), C2 (HL)) at the highlight point and the color difference amounts (C1 (SD), C2 (S
D)).

Based on the color difference amount of the highlight point and the color difference amount of the shadow point, as shown in FIG.
Can be inferred.

As shown in FIG. 12A, the color solid of an ideal image in which the color balance is not shifted has the color solid axis I matched with the lightness axis Y.

Therefore, in the color balance correction of the present embodiment, a rotation matrix and a translation amount for converting the color solid axis I (defined by highlight and shadow point) of the input object image into the lightness axis Y are obtained. The color balance of the input image is corrected by correcting the input object image using the rotation matrix and the translation amount.

The rotation matrix can be easily obtained if the rotation axis and its angle are determined.

As shown in FIG. 12, (C) of each pixel of the input image
1, C2, Y) in a three-dimensional color space, and FIG.
(C1 ', C2', Y '). In this way, the color balance of the image is corrected in a three-dimensional color space.

(Adjustment of Contrast and Saturation) Next, adjustment of contrast and saturation will be described. That is, a method of simply determining whether the image is overexposed or underexposed and applying gamma to the luminance signal accordingly will be described.

To adjust the contrast, the brightness of the shadow point is set to "0" or a value close to it (for example, "10") and the brightness of the highlight point is set to "255" or close to it by gamma correction according to the exposure state of the image. It is adjusted to a value (for example, “245”). An example in which over-under of the exposure of the image is simply determined and gamma corresponding to the over-under is applied will be described.

First, a point which is the minimum distance between the color solid axis and the luminance axis of the image, that is, T and T 'in FIG. This can be easily obtained from the geometric relationship.

Then, the contrast is adjusted so that T ′ becomes T. That is, as shown in FIG. 13, (T, T ′)
If Y ′ is smaller than T ′, Y ′
If the axis of the image is parallel to the luminance axis, T itself becomes nonsense. For example, when the axis of the image is parallel to the luminance axis, T itself becomes nonsense. May be corrected by I2.

The effect of the correction by T and T 'is considered to act particularly on an overexposed or underexposed image. Overexposure means that the whole is pulled into a bright place such as the sky, but at this time, input devices such as digital cameras perform high-brightness color suppression,
The saturation of the high luminance part is reduced.

That is, the color solid axis of the image is shown in FIG.
As shown in (a), when considered on a two-dimensional plane having the saturation and luminance as axes, a portion of high luminance appears to be closest to an achromatic color.

Conversely, low luminance color suppression is applied to an under image, so that the result is as shown in FIG. Therefore,
It is possible to easily determine whether the image is over or under based on the values of T and T '.

When the luminance axis of a color solid is considered on a luminance-chroma plane in an actual image, an overexposed image is as shown in FIG. 14C, for example. Conversely, an under image is, for example, as shown in FIG.

In the first place there should be (in an ideal state)
If you think that the actual color solid deviates from the color solid due to some shooting conditions or input (A / D conversion),
The positions of T and T 'are considered to be the places where the deviation is the smallest. Therefore, in this embodiment, appropriate gray is simply corrected by returning this, that is, the overall brightness is corrected.

The saturation adjustment can be performed very easily. For example, when increasing the saturation by 20%, the processing of C1 ″ = 1.2 × C1 ′ C2 ″ = 1.2 × C2 ′ is performed. Can perform the saturation correction. this is,

[0044]

[Outside 1] By being defined by.

The degree of saturation adjustment may be determined based on a user's instruction set on the user interface of the printer driver.

As described above, the image correction processing according to the embodiment of the present invention is performed on the luminance / color difference space.

Therefore, the correction parameters used in the image correction processing include a parameter 1 for converting an input RGB signal into a luminance / chrominance signal, a color balance correction in a luminance / chrominance space,
This is a three-dimensional LUT created based on parameter 2 for performing contrast correction and saturation correction and parameter 3 for converting a luminance / color difference signal into an RGB signal.

Parameter 2 is a rotation matrix described in color balance correction, a table for converting luminance components as shown in FIG. 13 described in contrast correction, and a color difference signal corrected in color balance described in chroma correction. It is composed of coefficients that

The table for converting the rotation matrix and the luminance component is obtained based on the histogram of the luminance component of the object image.

(3) Color Matching Processing The color matching module 111 performs a color matching process using a source profile corresponding to the input color information included in the drawing command and a printer profile corresponding to the printer. Convert to color information.

When a profile is added to the header part of the function of the drawing command, the added profile is used as the input profile. If no profile is added, a profile corresponding to the system monitor set in the host computer 100 is used, or a profile corresponding to the setting by the printer driver is used.

The color reproduction range of the printer is narrower than the color reproduction range of the monitor. Therefore, the color indicated by the input color information may not be able to be faithfully reproduced by the printer. Therefore, in the color matching processing, the input color information is converted into printer color information indicating colors within the color reproduction range of the printer by using a color matching processing method corresponding to the type of the image indicated by the input color information.

As a color matching processing method, “color priority (perceptual)”, “vividness priority (Saturatio)
n) "and" Colorimetric ".

“Color tone priority” is a color matching processing method suitable for a photographic part, which emphasizes the color tone and color gradation of an image and preserves the gradation of colors outside the color reproduction range of the printer. The entire image is mapped within the color reproduction range of the printer.

"Vividness priority" is a color matching processing method suitable for a graphic portion, which emphasizes the reproduction of vivid colors of an image and preserves the chroma components of colors outside the color reproduction range of the printer as much as possible. In the color gamut of the printer.

"Colorimetric matching" is a color matching process suitable for a text image such as a character or a logo generated by a user designating a specific color on an application. In this color matching processing method, mapping is performed so as to minimize the color difference (ΔE) in order to faithfully reproduce a specific color.

(4) Rasterization processing Based on the color information on which the image correction processing and the color matching processing have been performed, the RG corresponding to the resolution of the printer is obtained from the drawing command.
B raster data is generated and rasterized sequentially in an RGB 24-bit page memory.

(5) Printer Color Processing The RGB raster data is subjected to brightness / density conversion processing, masking processing, gamma processing, and N-value processing, and is converted into CMYK data corresponding to the recording material CMYK used in the printer. .

Hereinafter, the flow of processing of the printer driver according to the embodiment of the present invention will be described with reference to FIGS. 2 and 3.

The printer driver requests the application or the OS twice for print data (drawing command group) constituting the print page image. In response to the first and second requests, the application issues all drawing command group sets necessary to output a page.

FIG. 2 shows the first print data processing flow, and FIG. 3 shows the second print data processing flow.

In the first print data processing flow, print data is analyzed to collect information necessary for image correction processing, and preparations for execution of image correction processing are made. In the second print data processing flow, the image correction processing is performed only on the portion of the image drawing command determined to require the image correction processing, using the preparation result of the execution of the image correction processing prepared earlier, and color matching is performed. A correction process is performed, the drawing command is rasterized in a page memory, a print image is created, and the print image is transferred to a printer.

The first print data processing flow shown in FIG. 3 will be described.

At step S10, drawing commands are received one by one from the application or the OS. At step S20, the contents of the drawing command are analyzed, and the type of the object image indicated by the drawing command is identified. If the drawing command is different from the image drawing command such as text or graphics, it is determined that the type of the object image is not a photograph, and the process proceeds to S30.
In the first processing flow, nothing is performed (S4
0), and proceed to S100.

If it is determined in step S20 that the print data is an image drawing command, the flow advances to step S50. The image correction process used in the present embodiment is a process for correcting a color balance that has been destroyed due to the influence of shooting conditions or the like, and thus is a photographic image. Generally, photographic images are often 24-bit RGB object images, and image images with a smaller bit depth (for example, an 8-bit palette) are often not original photographs, and are not appropriate for correction processing. . For this reason, the header of the function of the image drawing command is referred to in S60, and the process proceeds to S70 only when the bit depth of the image is 24 bits or more.

Next, in step S70, the header of the function of the image drawing command is referred to, and if the Intent has been designated, the value is referred to, and the "color priority" Intent which is appropriate for the natural picture is designated. S8 as processing target if
Go to 0. However, even if the bit depth of the image is 24 bits, for example, if "colorimetric match" is specified, the image content is a company logo, or if "saturation priority" is specified May be a banner image of a jpeg image on the Internet homepage, and may not be a natural image photograph, so that processing is not performed and the process proceeds to S100.

Next, in S80, the contents of the object image passed by the image drawing command are sampled. In the correction logic used in the present embodiment, it is sufficient to obtain an outline of the luminance histogram of the object image. Therefore, when the object image has a certain size or more, it is not necessary to sample all the pixels. The quality of the result does not change even if sampling is performed while thinning is performed. Therefore, in S80, the processing speed is increased by determining the sampling thinning rate based on the size of the object image and performing the thinning sampling.

For example, if the size of the object image is 100
If it is x100 pixels, all pixels are sampled to create a luminance histogram, but if it is 200x200 pixels, processing is performed every other line, and sampling is performed every other pixel in each processing line.

For example, if the width of an object image is W, the height is H, and the thinning ratio in the vertical and horizontal directions is SkipX and SkipY, then SkipX = (W / 100) +1 SkipY = (H / 100) +1 In a simple way.

The method of obtaining the thinning rate is not limited to this, and a value suitable for the correction logic to be used may be applied.

Next, in S90, one entry is created in the table [] shown in FIG. 4 in the RAM, and the sampling processing result created in S80 and the drawing command information included in the image drawing command are stored.

Drawing command information I stored in table []
FIG. 5 shows an example of the contents of mageInfo.

The contents of ImageInfo are the drawing position X, Y, width W, height H,
The bit depth of the object image, the Source Color Space information specified by the CMS, the color matching Intent specified by the CMS, and the like.

Source Color Spac included in the ImageInfo
FIG. 6 shows an example of the content of the e information.

The content of the Source Color Space is an ICC profile that stores a gamma value and a white point value assumed by the RGB 24-bit value of the object image and various information indicating characteristics on which the RGB 24-bit value depends.

The processing from S10 to S100 is repeated until the above processing is completed for all the drawing commands in S100, and when the processing of all the print data is completed, the process proceeds to S110.

When the process reaches S110, entries are created in the table shown in FIG. 4 by the number of image drawing instructions indicating the object image to be subjected to the image correction processing included in the output page. Each entry has drawing instruction information ImageInfo and sampling information HistInf of each object image.
o is stored. In S110, the rendering command information ImageInfo of all the entries in the table are compared with each other, and one image is divided by the application to group objects that are a plurality of image rendering commands.

FIG. 8 shows an example of a document created by the application. In this example, a page is composed of one text object, two graphics objects, and six image objects.

Of these, the text object and the graphics object correspond to S30 in FIG.
To the table and no entry is created in the table. Further, since image 1 in FIG. 8 is an 8-bit palette image, the determination in step S60 of FIG. 3 is NO, and no entry is created in the table. Images 2, 3,
A total of five image drawing commands 4, 5, and 6 are shown in FIG.
To create an entry in the table.

That is, in the page shown in FIG. 8, when the process reaches S110 in FIG. 2, a total of five entries are created in the table.

The user of the application shown in FIG. 8 pastes three images at the time of document creation. One is image 1, and one is internally divided into image 2 and image 3 by the application. One is internally divided into image 4, image 5, and image 6 by an application.

In some applications, the pasted object image is treated as one object image internally as it is, and one image drawing command is issued at the time of output. However, in a relatively high-grade application for optimizing the use efficiency and processing speed of a memory, a large image may be internally divided and processed by a plurality of image drawing commands as shown in FIG. For example, it is well known that this process is performed by Adobe PhotoShopv4.0 or the like.

In the present embodiment, since a histogram is created independently for the image rendering command for correction processing, in the case of the page of FIG.
Essentially, a different histogram is created for one part of an image, for each part internally divided by the application.

For example, in the photograph portion of “landscape” in FIG. 8, the image 4 portion has many “bright sky” and the image 6 portion
The part is often "dark ground". Correction parameters derived from the results of the respective histograms are naturally different.

Therefore, when correction parameters are obtained from each histogram and image correction is performed, image correction processing is performed on each part using different correction parameters. As a result, in an area where an output image should be a single image, a color tone shift may occur at a boundary between parts.

Originally, it is inappropriate for the application to perform various correction processes for each internally divided part of one image from the viewpoint of the image quality of the output image.

In order to avoid this problem, it is recognized that the image 4, the image 5 and the image 6 are originally one image object image, and each of them is a group forming a part of the constituent elements. Needs to be synthesized. Then, a plurality of histograms of the group are combined to obtain a combined histogram for the entire group, a correction parameter to be applied to the entire group is calculated from the combined histogram, and image correction processing using the same one correction parameter is performed for the entire group. You need to do it.

Various methods are conceivable for grouping the entries stored in the table in S110.

A simple example will be given. ImageInfo of all entries in the table are mutually referred to, and the drawing position information X, Y,
Entries determined to be adjacent to each other as determined from W and H are determined to be in the same group.

For example, image 4 and image 5 in FIG.
Since the respective X and W values match, and the Y + H of the image 4 matches the Y of the image 5, it can be seen that they are vertically adjacent to each other. Similarly, it can be understood that the image 5 and the image 6 are vertically adjacent to each other, and as a result, it can be determined that the image 4, the image 5, and the image 6 visually constitute one image as one group.

FIG. 9 shows the contents of the table in which the group ID is determined as a result of this determination.

Indexes 0 and 1 correspond to image 2 in FIG.
The index 2, 3, and 4, in which the same group ID = 0 is set, are the entries of image 4, FIG.
5, 6 and the same group ID = 1 is set.

According to this determination, the table has five entries, but the group is classified into two.

As another method of performing grouping, in addition to the image position, more strictness can be obtained by adding a match of the bit depth of ImageInfo to the condition or a match of the specified Source Color Space to the condition. Grouping is possible.

For example, when a document is laid out by a user of an application so that two object images having the same size happen to be vertically adjacent to each other, two different images can be formed by grouping only the drawing position information. In some cases, the groups are determined to be one group, and the histograms are combined, and an appropriate correction parameter may not be obtained. However, if the two object images are obtained from different input devices, for example, one of the source color spac
e is specified, and the other is
Source Color Space is specified. Therefore, by judging the coincidence of the designated Source Color Space, it can be recognized that the image is another independent image.

As another grouping recognizing method, for example, a printer driver prepares a list of names of applications that perform image division as a database, extracts the name of the application that is performing printing at the time of printing, and obtains an application that does not perform image division. In some cases, grouping is not performed.

As another grouping recognition method, for example, a print image is displayed on a monitor as a preview screen,
It is conceivable to provide an interface for confirming the grouping result with the eyes of the user and, when there is an erroneous recognition, explicitly specifying the group ID of each image manually by the user. Regarding the method of displaying the print image on the preview screen, the method of “ColorAdvisor”, which is an application for previewing the print output to the market product Canon BJ Printer Driver and changing the color of the text part by the user, is generally good. Are known.

As another grouping recognition method, there is an example in which the divided images overlap each other with an overlapping portion instead of adjacent ones depending on the application. In order to cope with this, judgment is made based on the drawing position information of ImageInfo. There is also a method of saying, "If there are overlapping parts, they belong to the same group."

The method of grouping may be arbitrarily switched according to the application to be used. Any method can be used as long as the same group ID can be assigned to the entry of each part of the divided image. No problem.

At S110, for example, the group shown in FIG.
When the grouping process is completed as in the case of ID, the next
In the sampling information Hist with the same group ID
Performs Info composition processing. In the synthesis processing of the sampling information, frequency information for the same luminance is simply added. For example, the entries of indexes 0 and 1 having group ID = 0 are Histgram1 and Histgram2 in FIG.
If the “histogram” in the “fo” has the “luminance histogram”, the two histograms are synthesized and Histgram 0 (HistIn
fo0).

As a result, the indexes 0 and 1 of the table
Are combined to have the same sampling information HistInfo0 (FIG. 9).

Similarly, the three histograms of indexes 2, 3, and 4 are also synthesized, and all three have the synthesized sampling information HistInfo1 having the same contents (FIG. 9).

Next, in S130, a correction parameter used in the above-described image correction processing is calculated from the luminance histogram of the grouped images, and the calculation result is stored in HistInfo of the entry of the table.

Thus, the first print data processing flow shown in FIG. 3 is completed, and the printer driver requests the OS or the application to transmit the second print data.

FIG. 3 shows the second print data processing flow.

As in the first print data processing flow, S
At step 200, print data (drawing command) is received one by one from the application or the OS. At step S210, the contents of the drawing command are analyzed. If the drawing command is not an image drawing command such as text or graphics, step S22 is executed.
0, the process proceeds to S260, performs a color matching process according to the type of the object, and performs rasterization in the page memory in S270.

In the case of an image drawing command in S210,
Proceed to S230.

In S240, whether the image drawing command is an object entered in the table is determined by its drawing position, bit depth of object image,
lorSpace information, Intent value of table entry ImageI
Compare with the information stored in nfo and search for the one that matches all. If it is not registered in the entry, the process proceeds to S260, where a color matching process is performed, and in S270, rasterization is performed on the page memory.

If a matching entry exists in the table in S240, the process proceeds to S250. Im in S250
His of entry of table where ageInfo matches all
Using the correction processing parameters stored in tInfo, image correction processing is performed on the object image requested to be drawn by the image drawing command.

In S250, the color image processing of “color priority”, which is the color matching processing corresponding to the photograph, is performed on the object image subjected to the correction processing in S260, and rasterized in the page memory in S270.

In S280, it is determined whether or not all the print data has been processed, and the above-described processing in S200 to S280 is repeated until the processing of the print data for all pages is completed.

If it is determined in step S280 that the processing of all print data has been completed, the flow advances to step S290 to perform printer color processing on the print image data created in the page memory, so that the printer can output. To a nice image.

At S300, the print image converted into an image that can be output by the printer is processed into print data that can be processed by the printer and transferred. Normally, in a raster printer, data is compressed one raster line at a time and packed into a simple printer command for transfer.

(Second Embodiment) In the first embodiment, the color matching process in the printing process is performed as one of the color processes of the printer driver. In the present embodiment, a process will be described in which the application 101 that performs color editing or the like performs color matching processing on an input image using a color matching module.

In the application, the fact that the color matching processing has been performed on the input image in advance is as follows.
It is considered that the user has completed color correction on the image using the application. Therefore, performing the image correction processing and the color matching processing in the printer is inappropriate because the color correction satisfied by the user may be lost.

Therefore, in the present embodiment, when the header of the function of the drawing command indicating the object image input by the printer driver includes information indicating that the color matching processing has already been performed, the object The image correction processing and the color matching processing described in the first embodiment are not performed on the image.

According to the second embodiment, the color processing of the printer driver can be controlled based on the color processing performed by the application, and a high-quality image can be output.

(Modification) In the above embodiment, the image correction processing (color balance correction, contrast correction, saturation correction) based on the histogram is performed as the image correction processing.
The sampling processing method and the grouping processing method in the embodiment of the present application can be applied to other image processing.

For example, in the embodiment of the present invention, color matching processing is performed using a color matching method stored in advance in a profile. However, it is also possible to dynamically create color matching processing conditions according to an input image. 04-260121. By applying the sampling processing method and the grouping processing method in the embodiment of the present application to dynamically set a color matching processing method according to an input image, good color matching processing conditions can be obtained at high efficiency.

In the above embodiment, the print request is issued twice to the application. However, the present invention is not limited to this. The drawing command input in the first print request is stored, and the second print request is required. You may not make it.

Further, in the above-described embodiment, the mode in which the image correction processing is performed in the printer driver has been described. However, the present invention can naturally be performed by the monitor driver. Moreover,
The image correction processing can be performed by a color correction application.

Although the above embodiment has been described using a raster driver as a printer driver, the present invention can be applied to a printer driver compatible with a page description language such as PostScript.

The present invention can be applied to a system composed of a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.) or to an apparatus composed of one device (for example, a copying machine or a facsimile machine). May be.

In the above-described embodiment, the brightness histogram is created. However, the histogram may be created based on other brightness components such as luminance.

Also, in the color matching processing of the above-described embodiment, it has been described that the profile is added to the header part of the drawing function, but the header part of the drawing function is simply information for reading the profile stored in the memory. May be stored.

Further, it may be possible to manually instruct whether or not to perform the image correction processing on the user interface of the printer driver.

In addition, software for realizing the functions of the above-described embodiments is provided to a device or a computer in a system connected to the various devices so as to operate the various devices so as to realize the functions of the above-described embodiments. The present invention also includes a program code supplied and executed by operating a computer (CPU or MPU) of the system or apparatus according to a stored program to operate the various devices.

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

As a storage medium for storing such a program code, for example, a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, magnetic tape, nonvolatile memory card, 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 code. Needless to say, the program code is included in the embodiment of the present invention even when the functions of the above-described embodiment are realized in cooperation with application software or the like.

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

[0132]

According to the first aspect of the present invention, a good output image can be obtained by setting the same color processing conditions for one image.

According to the second aspect of the present invention, the color processing conditions can be efficiently obtained by setting the sampling conditions according to the image data size.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an example of a system configuration.

FIG. 2 is a flowchart illustrating a first print data processing flow;

FIG. 3 is a flowchart illustrating a second print data processing flow.

FIG. 4 is a diagram showing a configuration example of a table.

FIG. 5 is a diagram showing a configuration example of an Image Info value.

FIG. 6 is a diagram illustrating a configuration example of a Source Color Space.

FIG. 7 is a diagram showing a configuration example of a Histogram Info value.

FIG. 8 is a diagram showing an example of an input image.

FIG. 9 is a diagram showing an example of a table at the end of a first processing flow.

FIG. 10 is a diagram illustrating a histogram combining process.

FIG. 11 is a view for explaining how to obtain highlight / shadow luminance;

FIG. 12 is a diagram illustrating the principle of color balance correction.

FIG. 13 is a diagram illustrating contrast adjustment.

FIG. 14 is a view for explaining characteristics of overexposure / underexposure as viewed in a luminance-chroma plane.

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor: Manabu Yamazoe F30 terms within Canon Inc. 3-30-2 Shimomaruko, Ota-ku, Tokyo 5B057 CA01 CA18 CB01 CB16 CE11 CE17 DC23 5C077 LL04 LL19 LL20 MP06 MP08 PP06 PP32 PP35 PP37 PP52 PP53 PP65 PQ22 TT02 5C079 HA13 HB01 LA02 LA06 LA12 LA19 LB02 MA01 NA03 NA04 NA05 PA03

Claims (11)

[Claims] 1. An image processing method for performing color processing according to an object image, comprising: inputting image data indicating a plurality of object images; analyzing a relationship between the plurality of object images; An image processing method, comprising: grouping a plurality of object images; and setting the same color processing condition for the plurality of object images belonging to the same group. 2. The image processing method according to claim 1, further comprising determining a color processing condition according to a color distribution of the plurality of grouped object images. 3. The image processing method according to claim 1, further comprising: creating a histogram for each of the object images; and combining a plurality of histograms based on a result of the grouping. 4. The image processing method according to claim 1, wherein the object image is indicated by a drawing command, and the analysis is performed based on header information of the drawing command. 5. An input unit for inputting image data representing an input image, a sampling processing condition being set according to an image data size of the input image, and a sampling of the input image data under the set sampling condition. An image processing method for obtaining processing conditions by analyzing the sampled image data. 6. The image processing method according to claim 5, wherein the image data is represented by a drawing command, and the image data size is obtained based on header information included in the drawing command. 7. An image processing apparatus for performing color processing according to an object image, comprising: inputting image data representing a plurality of object images; and analyzing means for analyzing a relationship between the plurality of object images. Grouping means for grouping a plurality of object images based on the analysis result; setting means for setting the same color processing condition for the plurality of object images belonging to the same group; and the set color processing condition A color processing unit for performing color processing on the object image based on the image processing. 8. The image processing apparatus according to claim 7, wherein the color-processed object image is formed on a recording medium.
The image processing apparatus according to any one of the preceding claims. 9. An input unit for inputting image data indicating an input image; a setting unit for setting a sampling processing condition according to an image data size of the input image; and the input image based on the set sampling condition. An image processing apparatus comprising: sampling means for sampling data; and means for obtaining a processing condition by analyzing the sampled image data. 10. A recording medium for recording a recording medium for realizing an image processing method for performing color processing according to an object image, comprising: inputting image data indicating a plurality of object images; Analyzing a relationship between the images, grouping a plurality of object images based on the analysis result, and recording a program for setting the same color processing condition for the plurality of object images belonging to the same group. recoding media. 11. A recording medium for recording a program for realizing a process for setting a processing condition, wherein a sampling process condition is set in accordance with an image data size of an input image, and A recording medium recording a program for obtaining processing conditions by sampling input image data and analyzing the sampled image data.