JP2002281337A - Image processor, program for executing image processing function, and recording medium recoded with the program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To perform color transformation processing by selecting the most advantageous system in processing speed and adaptive processing precision when color reproduction is optimized. SOLUTION: A color transformation procedure deciding part (303) decides color transformation procedures based on the characteristics of an image. For example, when the number of pixels of image data is more than N-fold of the number of color transformation parameters, a procedure to change a color transformation parameter is selected and the color transformation parameter matching the compensation contents (304) is set (306).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus and, more particularly, to an image processing apparatus which corrects the color tone of a digital color image photographed by a digital camera or the like according to its characteristics, and optimizes color reproduction in a color image output apparatus. A printer that converts an input color image signal such as image data obtained by reading a photographic film or image data obtained from a digital camera into an image recording signal to be sent to a color image output device such as a color printer. This technology can be applied to controller devices, driver software for color printers, and image editing software.

[0002]

2. Description of the Related Art In a multimedia system mainly including a host computer, a color matching system (CMS) for performing color matching processing of image data between an input device and an output device has been actively developed.

[0003] ColorSync ™ of Apple Inc., which is a typical CMS framework, uses a color space (Device Dependent Colo) that depends on an input device.
rSpace) is converted into a device independent color space (Device Independent Color).
Space), and further converts an image signal in a device-independent color space into a color space that depends on an output device, thereby realizing a common CMS on the system.

[0004] Data representing conversion characteristics for this conversion process is called a profile, which is prepared in a host computer for each device, and an image signal is automatically or manually selected at the time of conversion according to the conversion characteristics of the profile. Is converted.

In the above-described color matching system, since the input signal is color-converted into the output signal via a device-independent color space, colorimetrically consistent color reproduction can be performed.

On the other hand, with the spread of the Internet and the intranet, the sharing of documents is progressing, and there is an increasing demand to be able to accurately grasp colors even on a remote computer. Therefore, the photo image data and the like are corrected in advance and attached to the document, and the color management information of the photo image is added and stored / stored, and when viewing in a remote environment, the above-described CMS architecture is used. Functions such as display according to the monitor characteristics of a remote computer have begun to be provided in some applications.

As described above, while a platform for accurate color reproduction is prepared, digital photographic image data is rapidly spreading with the spread of scanners and digital cameras. When printing out such photographic image data, he would like to make use of the characteristics of digital images to make color corrections according to his liking for images that are underexposed or backlit rather than accurately reproducing colors. There is an increasing demand, and there is a technology for optimizing the color reproducibility of a color printer or the like according to an input color image.

For example, in the apparatus described in Japanese Patent Application Laid-Open No. Hei 10-208034, RGB image data is analyzed and color tone corrected, and output to a printer through a printer driver, or displayed on a display screen through a display driver. I have to. Color tone correction is RGB
Automatically corrects the contrast by calculating the luminance distribution of the image and changing the correspondence between the luminance of the conversion source and the luminance of the conversion destination from a direct proportional state to a state in which the luminance is appropriately distorted into an S-shape based on the standard deviation. In addition, the contrast correction process is not performed by performing a binary image determination or a business graph based on the state of the luminance distribution.

In the apparatus described in Japanese Patent Application Laid-Open No. H11-161772, standardized conversion is performed by referring to the characteristics of an input device, "subject information" specified by an operator, and the characteristics of a document, in addition to the analysis result of an input image. Parameters are determined, and standardization conversion suitable for an input image is performed using the parameters. Also, when a standardized image is subjected to recording conversion and output, similarly, a recording conversion parameter is determined according to the analysis result of the standardized image and various image quality management information, and the parameter is used.

In the apparatus described in Japanese Patent Application Laid-Open No. 10-200778, the number of colors of an input image is detected, and when it is determined that the input image is a natural image, a grid point table for color conversion is changed before the color conversion. When it is determined that the image is not a natural image, the color conversion using the cache is performed without changing the grid point table.

[0011]

As described above, there have been proposed many methods for automatically adjusting the color tone of an image or a scanner image of a digital camera and converting the image into output data. However, since it is necessary to analyze arbitrary input image data and then perform color adjustment, and further to perform color conversion to a control signal for a color image output device such as a color printer, the processing time becomes longer, and the time required for image output is increased. There was a problem that it took a lot of time.

For example, each pixel of input image data configured in a bitmap format is subjected to adaptive processing such as automatic correction of contrast in accordance with the feature amount of the entire input image, and is a control signal of a color printer. CMY
(K) When performing color conversion to a signal, as the number of pixels (size) of an image increases, the processing load due to performing image adaptation processing increases as compared with normal color conversion.

In addition, after updating color conversion parameters for a color image output device, such as a masking coefficient and a grid point table in the input color space, according to the feature amount of the entire input image, normal color conversion is performed. When the input image data has a low resolution and a small number of pixels, or for an image with a small number of colors such as computer graphics, the color conversion parameters are changed or recalculated to obtain the entire image data. The processing load becomes large, and much time is required until image output.

In addition, if a method of performing color conversion by selecting from a plurality of color correction parameters does not increase the processing time as described above, it is impossible to optimally reproduce an input image having various characteristics. Can not.

Still another problem is that the input image data has a low resolution and the number of pixels is extremely small, or an image with a small number of colors, such as computer graphics, is automatically corrected in accordance with the characteristic amount. In the processing, if the color distribution is discrete, there is a problem that the color is not properly adjusted.

The present invention has been made to solve the above-mentioned conventional problems, that is, the present invention efficiently optimizes the color reproducibility in a color image output device according to the characteristics of an input color image. Accordingly, an object of the present invention is to reduce processing speed and adaptive processing when optimizing color reproduction in a color image output device according to an input color image. An object of the present invention is to provide an image processing apparatus capable of selecting the most advantageous method in terms of accuracy and performing color conversion processing.

Another object of the present invention is to optimize the color reproduction in a color image output apparatus according to an input color image, and it is most advantageous to consider the color distribution of the image in processing speed and adaptive processing accuracy. It is an object of the present invention to provide an image processing apparatus capable of performing a color conversion process by selecting a suitable method.

[0018]

According to the present invention, there is provided an image processing apparatus for optimizing color reproduction in a color image output device in accordance with input color image data, the analyzing means for analyzing characteristics of the input color image data. A first unit for changing a color conversion parameter for the color image output device; a second unit for correcting a color tone of the input color image data; and a change of the color conversion parameter and the color tone correction. A third unit that is not implemented; and a selecting unit that selects any one of the first, second, and third units based on the analysis information of the analyzing unit.
At least the number of color conversion parameters is included.

[0019]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be specifically described below with reference to the drawings.

FIG. 3 shows the configuration of an image processing apparatus to which the present invention is applied. In FIG. 3, reference numeral 103 denotes a computer for controlling the image processing apparatus 200.
Upon receiving an output instruction from the operator, the computer 103 converts the captured image data or the document data with the image data attached by capturing an image into a series of drawing data and transmits the series of drawing data to the image processing apparatus 200. .
The image processing apparatus 200 temporarily stores the drawing data transmitted from the computer 103 in the buffer memory 201, converts the drawing data into print data that can be interpreted by the image output apparatus, and transmits the print data to the image output apparatus 104.

As an example of the process of converting to print data,
First, the drawing data interpreting means 202 reads out the drawing data from the buffer 201, and transmits the data to various image processing means while interpreting the attributes of the drawing data. For example, in the case of drawing graphics, a drawing command is sent to the graphics image processing means 203, and in the case of drawing an image, a drawing command is sent to the image processing means 204. The data subjected to the appropriate color conversion by the various image processing means is aggregated into one-plane raster data by the raster image generation means 206, and then necessary for communication with the image output device 104 by the transmission data generation means 207. To generate final print data.

FIG. 4 is a diagram for explaining a specific system configuration example to which the present invention is applied. In FIG. 4, reference numeral 103 denotes the computer described above, on which various applications and software such as a printer driver are mounted. The digital camera 101 and the scanner 102 are input devices for capturing image data to be processed. The display 100 is an output device for displaying image data, and the color printer 104 is an output device for printing out image data. Note that a color copier or a color facsimile machine may be used instead of the color printer.

The image processing apparatus 200 may be mounted inside a color printer or in a computer. Alternatively, the print data may be sent to a printer after the print data is generated by being mounted in a printer control device provided independently of the color printer.

Further, the present invention can be executed by software. In that case, the present invention can be executed by a printer driver existing as a program in a computer.

FIG. 1 shows the configuration of an image processing means 204 for an image included in an image processing apparatus 200 according to an embodiment of the present invention. The image processing unit for image 204 analyzes at least the features of the image data, and generates a color conversion parameter (value of a grid point) for performing appropriate color tone correction, a color correction parameter setting unit 306, and a pixel of the input image. A color tone correction unit 305 that performs appropriate color tone correction every time is provided.

That is, a feature amount calculation unit 302 for analyzing image data and calculating a predetermined feature amount, the number of pixels of image data and the number of color conversion parameters related to color conversion of input color image data, or a change thereof Conversion procedure determination unit 303 that determines a color conversion procedure according to the amount of calculation required for
A correction content determining unit 304 that determines what kind of color correction is to be performed based on the feature amount of the input image; a color conversion parameter setting unit 306 for realizing the correction content of the correction content determining unit 304; A correction unit 305 is provided, and a plurality of output color components C (Cyan) and M (Magent) which are control signals for a color image forming apparatus such as a color copying machine.
a), a color conversion processing unit 307 that executes a color conversion process into Y (Yellow) and K (blackK).

The image data input to the image processing means 204 for image is more specifically RGB (green, green,
(Blue, red) gradation data, and the image format is a bitmap format. The number of gradations of each color component is generally 8 bits = 256 gradations.
Another gradation number such as 4 or 512 may be used.

Further, the image processing means for image 204 includes a halftone conversion means for converting into print data which can be output by the image output device 104 described in FIG. 3 and a resolution conversion means for converting the resolution. Is also good.

Next, the overall operation of the image processing means 204 will be described. First, the image data portion in the image drawing data is separated by the drawing data analysis device 202 and sent from the feature amount calculation unit 302 to the color conversion processing unit 307.

The color conversion processing unit 307 is a color conversion apparatus corresponding to color management, and performs a color conversion process using the color characteristic information of the input device and the color characteristic information of the output device. From the drawing data analyzer 202 to R
When the GB color characteristic information is transmitted, the detected color characteristic information is set as the input color characteristic, and when the image output device is a printer, the color conversion of the image data is executed using the color characteristic information of the printer as the output color characteristic. Will do.

From the RGB (green, blue, red) gradation data,
Output color components C (Cyan), M (Mazenta), Y
The conversion into (Yellow) and K (blackK) data is performed by color conversion into CMYK by memory map interpolation. As shown in FIG. 2, when the RGB space is used as the input color space, the memory space is divided into the same type of three-dimensional figure (here, a cube) and the output value P at the input coordinates (RGB) is used. Is determined by selecting a cube including the coordinates of the input, outputting the eight points of the selected cube on predetermined vertices (grid point values) and the position of the input in the cube (each Linear interpolation is performed based on the distance from the vertex). Here, in the case of the present embodiment, the output value P
Represents the C, M, Y, and K values, respectively, and measures the relationship between the actual input and output (L * a * b * -CMYK) in the coordinates (RGB) in the input space used for the interpolation calculation. Then, using this data, C, M, and RGB for RGB (L * a * b *) calculated by an arbitrary black generation process and the least square method, etc.
The values of Y and K are set in advance.

The color conversion method is not limited to the above-described method. For example, a computer may record the characteristics of the image display device in the header information of the image data and transmit it. When the control device is mounted inside a computer, for example, ICC (Inter Col
or Consortium) may be read and used.

The feature value calculation unit 302 receives the image data from the drawing data analysis unit 202 and calculates the feature value for performing the color tone correction described later. Simultaneously count the number of color conversion parameters related to color conversion of
The information is sent to the color conversion procedure determination unit 303. Here, the number of color conversion parameters related to the color conversion of the image data refers to the input coordinates (RG
B) This is the number of coordinates (the number of grid points) used (referenced) when obtaining the output value P, and represents the color distribution of the image data. For example, when the color distribution of the image data is biased, only the grid point values of a specific area in the color space are referred to.

The color conversion procedure determination unit 303 determines (selects) a subsequent color conversion procedure from the following procedures according to the number of pixels of image data and the number of color conversion parameters related to color conversion. CM in the color conversion processing unit 307
Color conversion into YK signals is performed.

The first procedure is a procedure for realizing an adaptive process according to the characteristic amount of input image data by changing a color conversion parameter for a color image output device. For example, when the number of pixels of the input image data is N times or more the number of color conversion parameters related to color conversion, the color conversion procedure determination unit 3
03 requests the color conversion parameter setting unit 306 to change the color conversion parameter according to the correction content of the correction content determination unit 304. The change method is described in a correction content determination unit 304 described later.
There is a method of deciding by the above-described memory map interpolation using a correction value according to the correction content as an input value or a method of optimizing parameters by resetting a target value (for example, a grid point value according to the correction content) To change). The above multiple N is
It is determined based on the load (computation amount) required for the parameter change.

The second procedure is a procedure in which the color tone correction unit 305 realizes an adaptive process according to the feature amount of the input image data without changing the color conversion parameters. For example, when the number of pixels of the input image data is N times or less the number of color conversion parameters related to color conversion, the color conversion procedure determination unit 303 performs color adjustment of the bitmap data according to the correction content of the correction content determination unit 304. From the color tone correction unit 305.

The third procedure is a procedure in which neither the change of the color conversion parameter nor the color tone correction of the input color image data is performed. For example, if the number of pixels of the input image data is M
In the following cases, the ratio of the number of color conversion parameters related to color conversion to the number of pixels of input image data is K or less (the number of color conversion parameters related to color conversion is smaller than the number of pixels of input image data, that is, When the number is small, the default color conversion is performed without performing the adaptive processing according to the feature amount of the input image data (without sending information to the correction content determining unit 304).

The correction content determining unit 304 determines how to correct the image data based on the characteristic amount obtained by the characteristic amount calculating unit 302. Examples of correction content candidates include dynamic range correction, contrast conversion, color balance correction, and the like, but other methods may be used.

The above color conversion parameters include:
A gamma table for tone conversion or input RG
An ICC color profile that converts the B signal into an XYZ signal or the like may be used. Then, the obtained color conversion parameters are transmitted to the color conversion processing unit.

Next, a specific example of a series of color tone correction contents in the feature amount calculation unit 302, correction content determination unit 304, and color tone correction unit 305 will be described.

When automatic exposure and automatic white balance do not operate properly when photographing with a digital camera or the like, image data is transmitted from a digital camera or the like and output to an image display device or an image output device. Images often have poor tonal balance. For such an image having a poor gradation balance, the histogram (= frequency distribution) of the image is analyzed to automatically expand the dynamic range, change the contrast, and adjust the red, green, and blue colors. Several automatic image correction methods for adjusting the balance of color components have been proposed.

FIG. 5 is a diagram for explaining an example of a typical color tone correction method. First, in order to speed up the processing, image data is sub-sampled and reduced to reduce the number of pixels.
Next, the frequency distribution calculation means receives the image data and determines the frequency distribution of the gradation values for each color component. When the image data is represented by red, green, and blue components, a red gradation value distribution, a green gradation value distribution, and a blue gradation value distribution are obtained. However, when the storage device for storing the frequency distribution generation result has a limited capacity, the frequency distribution of the gradation values may be obtained for only one color component.

FIG. 6 shows an example of the luminance histogram obtained by the above processing. Then, a predetermined characteristic amount is calculated from the above-mentioned histogram, it is determined whether or not the image data has an appropriate gradation characteristic, and if necessary, the content of the color tone correction process is determined to generate a correction parameter. I do. The contents of general color tone correction processing include dynamic range correction, color balance correction, and contrast conversion.

First, in order to determine whether or not the dynamic range is appropriately obtained, the white luminance and the black point luminance of the input image are obtained as the characteristic amounts. For the white luminance and black point luminance, when the maximum value and the minimum value of the input image are used,
Considering the noise component, there are many methods such as a case where the cumulative frequency is 1% and the black point luminance is 1% and the 99% is the white luminance. If it is determined that the dynamic range is insufficient as a result of the dynamic range determination, the dynamic range is expanded by performing a level correction process. Further, there is an example in which the expansion range of the dynamic range is limited so that a night view image or the like is not converted more than necessary.

Next, the image having the color cast is discriminated and the color balance is corrected so as to remove the color cast. Various methods have been proposed for color cast correction. For example, since the color cast is conspicuous in a relatively bright portion of the image, an average of RGB is obtained as a feature amount for a high-brightness pixel in the histogram, and whether or not color cast has occurred is determined from the shift amount to determine the correction content. There are various ways to do this. In this case, parameters such as how much luminance is to be checked or how much deviation is determined to have caused color fogging are necessary, and these parameters are set in advance. For example, when ΔR = Rave−Gave ΔB = Bave−Gave, when ΔR> Rth, ΔB> Gth, it is determined that the color is cast, and the R component and the B component are set so that ΔR and ΔB become 0. On the other hand, gradation conversion is performed. Where R
ave, Gave, and Bave are the average values of the R, G, and B components present in 10% from the brightest of the histogram.

After performing the color balance correction, the exposure state is determined, and the contrast correction processing is performed as necessary. For example, when performing gradation conversion on an underexposed or overexposed image, the median or variance of the luminance value of the image data is obtained as a feature amount, and by determining these, whether the image is overexposed or underexposed is determined. Can be roughly determined.

FIG. 7 shows a configuration example when the processing functions of the present invention are implemented by software. In the color conversion system shown in FIG. 7, a workstation and a printer are connected. The workstation realizes the function of the above-described color tone correction processing, and includes a display, a keyboard, a program reading device, an arithmetic processing device, and the like. In the arithmetic processing device, a ROM and a RAM are connected by a bus to a CPU capable of executing various commands. Also, the bus includes DlSK which is a mass storage device,
An NIC that communicates with a device on the network is connected.

The program reading device is a storage medium storing various program codes, that is, a floppy (registered trademark) disk, a hard disk, and an optical disk (CD).
-ROM, CD-R, CD-R / W, DVD-ROM,
A device that reads program codes stored in a DVD-RAM, a magneto-optical disk, a memory card, or the like, such as a floppy disk drive, an optical disk drive, or a magneto-optical disk drive.

The program code stored in the storage medium is read by a program reading device and stored in DlSK or the like, and the program code stored in DlSK or the like is executed by a CPU to execute the above-described color conversion method or the like. It can be realized. When the computer executes the readout program code, an OS (operating system) or device driver running on the computer performs part or all of the actual processing based on the instructions of the program code. The case where the above-described function is achieved by the processing is also included.

[0050]

As described above, according to the present invention, the following effects can be obtained. (1) Since the color conversion method is appropriately selected according to the analysis information of the input color image data, when optimizing the color reproduction in the color image output device according to the input color image data, the processing speed and the adaptive processing The color conversion process can be performed by selecting the most advantageous method in terms of accuracy. (2) When optimizing color reproduction in a color image output device in accordance with input color image data, the most advantageous method is selected by considering the color distribution of the image in terms of processing speed and adaptive processing accuracy. A conversion process can be performed.

[Brief description of the drawings]

FIG. 1 shows a configuration of an image processing unit for images of the present invention.

FIG. 2 is a diagram illustrating a color conversion method.

FIG. 3 shows a configuration of an image processing apparatus to which the present invention is applied.

FIG. 4 shows a configuration example of an image processing system to which the present invention is applied.

FIG. 5 is a diagram illustrating a color tone correction process.

FIG. 6 shows an example of a luminance histogram.

FIG. 7 shows a configuration example when the processing function of the present invention is implemented by software.

[Explanation of symbols]

 202 Drawing data analysis device 204 Image processing means for image 302 Feature calculation unit 303 Color conversion procedure determination unit 304 Correction content determination unit 305 Color tone correction unit 306 Color conversion parameter setting unit 307 Color conversion processing unit

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Claims (5)

[Claims] 1. An image processing apparatus for optimizing color reproduction in a color image output device according to input color image data, comprising: an analysis unit for analyzing characteristics of the input color image data; First means for changing the color conversion parameter of the first color, second means for correcting the color tone of the input color image data, and third means for performing neither the change of the color conversion parameter nor the color tone correction, An image processing apparatus comprising: a selection unit that selects any one of the first, second, and third units based on the analysis information of the analysis unit. 2. The method according to claim 1, wherein the analysis information includes at least the number of color conversion parameters.
The image processing apparatus according to any one of the preceding claims. 3. An analysis function for analyzing characteristics of input color image data, a first function for changing a color conversion parameter for a color image output device, and a second function for correcting a color tone of the input color image data. Any one of the first, second, and third functions based on the analyzed information, and a third function that does not perform any of the color conversion parameter change and the color tone correction. A program for causing a computer to execute a selection function for selecting a program. 4. The program according to claim 3, wherein the analysis information includes at least the number of color conversion parameters. 5. A computer-readable recording medium on which the program according to claim 3 or 4 is recorded.