JP2001189862A - Image processing method and image processing device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing method capable of deciding the lightness of an image based on more detailed parameter of the lightness of the image, obtaining the degree of optimum correction to the image and especially increasing its density while maintaining the gradation of a high density part in a printed image. SOLUTION: In a histogram with respect to number of pixels as to each luminance of a luminance signal denoting the lightness of an image obtained from image data, the ratio (Slow) of the cumulative frequency of a prescribed low luminance area (0-X) to the entire pixel number is obtained, and in the case correcting the luminance by a gradation curve (γ=0.8) to darkly correct the luminance signal is used to correct the luminance, and when the ratio is higher than a prescribed value (Slow=20), the gradation curve is revised so as not to conduct correction (Σ=1) for the maintenance of the gradation for the luminance correction for the prescribed low luminance area.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and an image processing apparatus, and more particularly to an image processing method and an image processing apparatus for performing a luminance correction process on image data such as a digital photographic image. It is.

[0002]

2. Description of the Related Art In recent years, hard copy technology, especially full-color hard copy technology, is rapidly developing. In particular,
The printing technology by the ink jet system is becoming similar in printing quality to silver halide photography due to the reduction in graininess due to ink dots, and is widely spread due to its relatively simple printing system. . From such a point, it has become possible to faithfully reproduce a captured image or an image obtained by processing the captured image by using an inkjet printer and a high-pixel digital camera.

In such a system for printing a captured image, there is a problem that the density range that can be basically realized by a printer or the like, which is a printing device, is different from that of a digital camera or the like. For example, in the case of an ink jet printer, there is a problem that the density that can be realized in a high density portion is relatively lower than the density of a captured image. This is not limited to the case where a digital camera is used, but also applies to a system using an optical image reading device such as a scanner or a system for printing an image on a display such as a CRT. Then, due to the above-described essential problems, when an image captured or the like is printed, the image may be too bright or too dark compared to the actual color.

[0004] For this reason, the present applicant has proposed a method for coping with this, particularly by luminance correction processing in image processing. That is, basically, the luminance in the image data is corrected so that the ratio of the high-density area in the entire image is increased, thereby increasing the overall density of the print image so that the maximum achievable density of the printing device is relatively high. It is a proposal to make up for the low point. At this time, a histogram indicating the frequency of each luminance in the image data is used to determine the degree to which the luminance is corrected by the luminance correction (hereinafter, this is also referred to as “γ value”. Is analyzed, and the distribution of the high-luminance area and the low-luminance area is known based on the predetermined maximum luminance and minimum luminance in the histogram, and the degree of correction (correction condition) is determined accordingly.

[0005]

However, in the brightness correction processing for determining the γ value described above, the brightness distribution in the image data to be printed is determined based only on the highest brightness, the lowest brightness, etc. of the histogram. In some cases, an accurate luminance distribution cannot be grasped. For example, in spite of a relatively small low-luminance area (bright image), the above-mentioned predetermined minimum luminance itself has a comparatively high value due to a distribution peak around a relatively high luminance, It is determined that the image is relatively bright, and the γ value is set to a small value. As a result, the high-density portion image in the printed image may be lost.

[0006] In particular, even if an appropriate γ value can be obtained, if the correction is performed integrally in all the luminance regions using the γ value, the printed image obtained by correcting the high luminance region and the intermediate region is vivid. Color can be realized, but the gradation of the high-density part of the printed image due to the correction of the low-luminance area is not properly expressed,
Color so-called collapse may occur.

SUMMARY OF THE INVENTION The present invention has been made to further improve the above-described point, and an object of the present invention is to reduce the brightness of an image based on a more detailed brightness determination parameter in the image. Judgment, determine the optimal degree of correction for each image, and increase the density, especially while maintaining the gradation of the high-density part in the printed image, to achieve a more faithful reproduction of the image indicated by the image data. An object of the present invention is to provide an image processing method and an image processing apparatus that can be performed.

[0008]

According to the present invention, there is provided:
An image processing method for determining a correction condition for correcting a component related to brightness of the image data based on a histogram corresponding to a component related to brightness of an image indicated by the image data, and correcting the image data according to the determined correction condition A step of obtaining a ratio of the predetermined range of the component in the histogram in the histogram, and determining the correction condition based on the obtained ratio.

Preferably, the step of determining the correction condition includes, when the ratio is equal to or more than a predetermined value, changing the correction of the image data within a predetermined range of the component in the determined correction condition, and It is characterized in that the correction conditions are determined so as to perform the correction for maintaining.

In another aspect of the present invention, a correction condition is determined for a component relating to the brightness of the image data based on a histogram corresponding to a component relating to the brightness of the image indicated by the image data, and the correction condition is determined in accordance with the determined correction condition. An image processing apparatus for correcting image data, comprising: a determination unit that determines a ratio of a predetermined range of the component in the histogram in the histogram; and a setting unit that determines the correction condition based on the determined ratio. It is characterized by having.

Preferably, when the ratio is equal to or more than a predetermined value, the setting means changes the correction of a predetermined range of the component among the predetermined correction conditions and performs correction for maintaining the component value. The correction conditions are determined as described above.

According to the above arrangement, the ratio of a predetermined range of the component in the histogram is determined from the histogram corresponding to the component value relating to the brightness of the image, and the degree of correction of the component value is determined based on the ratio. At this time, when the ratio is equal to or more than a predetermined value, among the determined correction conditions, the correction of the component from the minimum value of the component to the predetermined component value is changed to perform the correction for maintaining the component value. Since the correction condition is determined, when the range from the minimum value to the predetermined component value occupies a large portion in the image, the correction for increasing the density of the print image is not performed, and thus the high density portion of the print image is not corrected. It is possible to increase the density of the entire image while preventing color collapse.

[0013]

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

<First Embodiment> FIG. 1 is a block diagram showing a schematic configuration of a printing system according to an embodiment of the present invention. This system is generally composed of a host computer 1
00, a printer 106 and a monitor 105. That is, the host computer 10
For example, an inkjet printer 106 and a monitor 105 are connected to “0” so that bidirectional communication is possible.

The host computer 100 has an OS (Operating System) 102.
An application 101 such as a word processor, a spreadsheet, an image processing, and an Internet browser, which performs each process under the management of the application 100, and various drawing commands issued by the application and indicating an output image (image drawing commands, text drawing commands, graphics A printer driver 103 that processes print rendering commands to create print data, and an application 101
Has a monitor driver 104 for processing various drawing command groups issued by the PC and displaying it on the monitor 106 as similar software.

The host computer 100 includes a central processing unit CPU 108, a hard disk driver HD 107, a random access memory (RAM) 1 as various hardware operable by the above-mentioned software.
09, a read only memory (ROM) 110 and the like. That is, the CPU 108 executes signal processing relating to processing according to the above-described software, and executes a signal processing on the hard disk or the R driven by the hard disk driver 107.
The OM 110 stores various kinds of software in advance, and reads and uses the software as needed. The RAM 109 is used as a work area for executing signal processing by the CPU 108 and the like.

As an embodiment shown in FIG. 1, for example,
A common example is a computer that uses Microsoft's Windows 98 as an OS, installs an application that can perform any print processing, and connects a monitor and a printer to an IBM AT compatible personal computer that is widely used. it can.

In the printing system having the above-described configuration, the user, based on the display image displayed on the monitor 105 by the application 101, similarly processes text data and graphics classified into text such as characters through processing by the application. Image data such as graphics data classified as graphics, image data classified as natural images, and the like.

When the user instructs a print output of the created image data, the application 101 issues a print output request to the OS 102, renders the graphics data portion with a graphics rendering command, and renders the image image data portion with an image rendering. A drawing command group indicating an output image, which is configured as a command, is issued to the OS 102. On the other hand, the OS 102 receives a print output request from the application, and issues a drawing command group to the printer driver 103 corresponding to the printer that performs the printing.

A printer driver 103 processes a print request and a drawing command group input from the OS 102 and
5 to create print data in a form that can be printed by the printer 1
Transfer to 05. In this case, if the printer 105 is a raster printer, the printer driver 103
The drawing command from S102 is sequentially subjected to image correction processing, rasterized sequentially into an RGB 24-bit page memory, and after all drawing commands are rasterized, the contents of the RGB 24-bit page memory are transferred to the printer 105.
Converts the data into a printable data format, for example, CMYK data, and transfers the data to a printer.

FIG. 2 is a diagram showing processing performed by the printer driver 103. The processing of the printer driver 103 is roughly divided into image correction processing and printer correction processing.

The image correction process 120 performs an image correction process on the color information including the luminance signals R, G, and B included in the drawing command group input from the OS 102. Specifically, based on the color information of red (R), green (G), blue (B),
An automatic gradation correction process described later is performed. On the other hand, the printer correction processing unit 121 first rasterizes the drawing instruction of the color information corrected by the image correction processing 120, and performs R, G, B
A raster image is generated in a 24-bit page memory.
Then, cyan (C), magenta (M), yellow (Y), and cyan (C) depending on the color reproducibility of a printer that performs printing for each predetermined pixel.
Black (K) data is generated and transferred to the printer 105.

Next, the automatic gradation correction processing as the image correction processing 120 will be described. The automatic gradation correction process is performed on an image image of the image data indicated by the image drawing command. Therefore, for example, when a graphics image or an image image is included in the image data, an image image portion is extracted from the image data, and an automatic gradation correction process is performed on the image portion.

FIG. 3 is a diagram conceptually showing mainly the conversion of each signal in the automatic gradation correction, and FIG. 4 is a flowchart showing the processing procedure. The automatic gradation correction according to the present embodiment is performed by determining the brightness of an image to be printed using a histogram in which the frequencies of the respective brightness values in the image data are totaled, and determining an appropriate degree of correction (γ value). Things. Hereinafter, this processing will be described mainly with reference to the flowchart shown in FIG.

(Histogram totalization) As shown in FIG. 4, in the histogram totalization processing in step S1, first, the input RGB image signal is converted into a luminance Y component, which is a component relating to the image brightness, and a component relating to the tint. (B1 in FIG. 3). The conversion formula is represented as follows. Y = 0.299 × R + 0.587 × G + 0.114 × B Cr = RY Cb = BY Next, of the converted signals Y, Cr, and Cb, the image of the signal Y corresponding to the luminance is obtained. The luminance value (signal Y value) of each pixel in the data is checked, and the frequency of the pixel having the luminance is totaled for each luminance value indicated by 0 to 255, and a luminance histogram (frequency distribution) is created. . The histogram created in this way is, for example, as shown in FIG. 5 when the image data shows an overall bright image, the distribution is biased toward the high luminance side, while when the image data shows an entirely dark image, As shown in FIG. 6, the distribution is biased toward the low luminance side. Note that the above-described creation of the luminance histogram is performed for the purpose of examining the frequency distribution of the luminance in the entire image. Therefore, the counting of the frequencies is not necessarily performed for all pixels. For example, 1600 (pixels) × 1200 (pixels) )
Image data of 15 (pixels) horizontally and 1 (vertically)
Aggregation may be performed on pixels thinned out by 1 (pixel), or an average value of each of those pixels with surrounding pixels may be used.

(Determination of Tone Curve) Next, in step S2,
A gradation curve determination process is performed based on the histogram obtained as described above. That is, it is determined what the gradation curve is, which is a correction curve corresponding to the γ value in the luminance correction. In the gradation curve determination of the present embodiment, the brightness of an image to be processed is determined by two parameters described below, that is, a highlight point and a γ parameter (the number of pixels in a low-luminance area), and γ is determined based on this.
A value, that is, a corresponding gradation curve is determined.

FIG. 7 is a flowchart showing the details of the γ determination processing, and the γ determination processing of the present embodiment will be described with reference to FIG.

Highlight Point Determination Unit In the highlight point determination processing in step S21, a highlight point in the image to be processed is calculated from the histogram (step S211).

In this embodiment, the highest luminance value (luminance value 255) in the luminance range in the above-mentioned histogram of the luminance signal Y.
From the above, the frequency of each luminance value is accumulated while sequentially going to the low luminance side, and the cumulative frequency obtained here is, for example, a luminance value that matches 1.0% of the total number of pixels of the image data to be processed,
Alternatively, first, a luminance value exceeding 1.0% of the total number of pixels is obtained, and this point is set as a highlight point (hereinafter, also referred to as “HLP”).

Next, the magnitude of the HLP obtained in this way is compared with the luminance value using a predetermined threshold Th, and when HLP> Th, the image is a bright image and H
When LP ≦ Th, the image is determined to be a dark image (step S212). That is, by this processing, the brightness is determined to be two types of images. The threshold value Th used in the present embodiment uses a relatively high luminance value, for example, 220 or the like.

For example, in the histogram of the bright image shown in FIG. 5, the HLP exceeds the threshold Th (HLP> T
h) Yes, and therefore, is determined to be a bright image. In this case, as described above, the distribution of the histogram is generally biased toward the high luminance side, and as a result, the HLP is also located on the high luminance side. On the other hand, in the histogram of the dark image shown in FIG. 6, the HLP is lower than the threshold Th (HLP ≦ Th), and the image is determined to be a dark image. In this case, such a determination is made because the luminance distribution is generally biased toward the low luminance side and the HLP is also located on the low luminance side.

As described above, the highlight point is determined from the histogram of the image to be processed, and the overall brightness of the image is determined based on the highlight point. Accordingly, the degree of correction, that is, the γ value, can be changed in relation to the distribution of the low-luminance area of the image to be corrected. For example, when the image is determined to be a dark image, the probability that the image is corrected with a smaller γ value (higher density; darker) than when the image is determined to be a bright image even if the distribution of the same low luminance region (the ratio of the low luminance region) Can be made lower, which makes it possible to print a dark image as a whole, for example, an image having a relatively small distribution of low-luminance areas at a low density, and to print a high-density portion in the printed image. Can be prevented from being collapsed. On the other hand, when the image is determined to be a bright image, on the other hand, the probability of correcting with a small γ value (enhancing the density; darkening) can be increased. It is possible to perform printing that compensates for the relatively low density output characteristics.

The HLP need not always be calculated by the above-described method, and a conventionally known method may be appropriately used.

Further, when performing the automatic gradation correction processing of this embodiment in combination with other image correction processing, for example, the so-called color fogging correction, contrast correction, and saturation correction, the image processing is performed in advance. HLP can also be used. In this case, instead of using the highlight point, the brightness (darkness) of the image can be determined by using the shadow point which is also used in the above color cast correction and the like, and based on this, the following processing is performed. It is obvious from the following description that the following can be performed.

Determination of the number of pixels in the low-luminance area (shadow area) (γ parameter determination) Next, in step S22, the histogram roughly determined in step S1 for the image roughly classified into two types of bright and dark by the highlight point determination Is used to determine the low-luminance area distribution.

[0036] In the pixel number determining process in the low luminance area, First, the S _low is the ratio of the cumulative frequency in a predetermined low-brightness area to the total number of pixels of the processing target image in step S221. This is because the degree of correction, that is, an appropriate value for the γ value, is obtained by obtaining the distribution of the low-luminance area in more detail, and in particular, the overall density is obtained without causing so-called collapse in the low-density part of the print image. Is to be increased.

First, as preprocessing, a cumulative frequency S in a low luminance area is obtained. The cumulative frequency S in this low luminance area is
In the histogram, it is obtained as a cumulative frequency from the lowest luminance value (luminance value 0) of the luminance range to a predetermined luminance value toward the higher luminance side. In this embodiment, the cumulative frequency up to a luminance value (luminance value 64) that is １ ／ of the maximum luminance value (luminance value 255) is obtained as the cumulative frequency S of the low luminance area.

Next, the ratio S _low of the cumulative frequency S of the low luminance area obtained as described above to the total number of pixels is calculated.

That is, here, S _low = (cumulative frequency S of low luminance area) / (number of all pixels) (%).

When the thinning histogram is created by thinning out the pixels at the time of the above-described histogram totaling, the denominator in the above-described _Slow definition expression is the number of pixels for which the histogram is created.

Next, in step S222, the γ value (γ parameter) is determined using the S _low obtained above.

This determination is, specifically, a process of determining the range to which _Slow belongs in the table shown in FIG. In other words, the range of S _low is different depending on the brightness of the image according to the above-described HLP determination. For the image determined to be a bright image, S _low = 0 to 30 and S _low = 3.
1 to 60 and S _low are classified into three ranges of 61 or more.
On the other hand, for the image determined as a dark image by the HLP determination, S _low = 0 to 15, S _low = 16 to 30, and S _low are 3
It is classified into one or more three ranges.

For example, in the case of a bright image shown in FIG.
The ratio of the shaded area to the total number of pixels is S _low . In this example, S _low is 10% of the total number of pixels. Therefore, the image is determined to be a bright image by the HLP determination, and S _low is determined to be in the range of 0 to 30. On the other hand, FIG.
In the region S _low indicated by hatched example of dark image shown in,
This is 40% of the total number of pixels. Therefore, the image is determined to be a dark image in the above-described HLP determination, and S _low is determined to be in a range of 31 or more.

Here, suppose that, as described above, without using the ratio of the cumulative frequency, the above-described shadow points (the respective frequencies are sequentially accumulated from the minimum luminance value in the histogram toward the high luminance side, and for example, the total number of pixels is calculated. When the method of judging the distribution of the low-luminance portion using only the luminance value which coincides with or exceeds 1.0% of the low-luminance portion is appropriately used, the actual distribution state of the low-luminance region is appropriately adjusted. A determination is made on the brightness of the image that is not reflected. For example, while the shadow point itself shows a relatively high brightness value,
Actually, if an image has a frequency distribution peak in the luminance value around the shadow point and the frequency distribution itself in the low-luminance area is small, it is erroneously determined to be a bright image and a small γ value (higher density) Brightness correction) is selected, and as a result, a dark portion occupying a relatively large portion on the image may be crushed.

On the other hand, as in the above-described embodiment, the cumulative frequency in the low luminance area is obtained, and the actual low luminance distribution is reflected by using the ratio S _low of the cumulative frequency to the total number of pixels. It is possible to determine the lightness and darkness of the resulting image, and it is possible to perform appropriate gradation correction on a darker image as described above.

In the above-described embodiment, the range of luminance values 0 to 60 is equally divided in the range of S _low . However, when more detailed information on the low luminance area is to be obtained, the low luminance area is divided into several parts. May be performed for each of the cases, and if S _low is 0 to 30, it is doubled and 31 to 60
Weights such as multiplying by 1 and adding up may be used.

Determination of Correction γ Value The range to which the ratio S _low of the low-luminance area belongs is determined by the above-described pixel number determination processing for the low-luminance area, so that the image to be processed becomes bright as shown in FIG. It is classified into a total of 6 types, 3 types and 3 types. Then, in the next step S23, the γ value is determined using the table shown in FIG.

In the present embodiment, the γ value is represented by a gradation curve shown in FIG.
As is clear from the (correction table), 0.8, 1.0 or 1.2 is set. Note that this γ value is brighter as described above (the density is lower in the printed image).
It indicates the degree of correction and does not indicate the ratio of correction to each input luminance value. The ratio of correction to each input value is represented by a curve representing each table in FIG.

The determination of the γ value for the images classified into the above six types is performed using the table shown in FIG.
When the determination is a bright image, γ = 0.8 when S _low = 0 to 30 and γ = 1.0 when S _low = 31 to 60
(That is, no correction), when S _low is 61 or more, γ = 1.
2 and so on. Specifically, as described later, a lookup table for correction corresponding to each γ value
(LUT) is prepared.

In the case of the bright image shown in FIG. 5, the HLP is larger than the threshold value Th and S _low is 10%.
Is determined to be a bright image, and the γ value is set to 0.8. By this γ value determination,
Darken up to relatively high brightness area (increase print density)
The correction is performed, and a print image having an optimum density as a whole is obtained.
Further, since the ratio of the pixels in the low-luminance area is small, the portion where the image is crushed can be reduced.

On the other hand, in the dark image shown in FIG.
Is smaller than Th and S _low is 40%, and the γ value is set to 1.2 according to the table shown in FIG. With this γ value setting, the whole image to be printed becomes brighter,
In particular, a low-luminance portion occupying 40% of the image becomes bright, and a printed image having a balanced density is obtained.

In the above description, in the highlight point determination, the brightness of the image is determined in two stages. However, in order to obtain a more optimal γ value, three levels, such as a bright image, an intermediate image, and a dark image, are determined. More detailed determinations may be made by dividing the cases into stages or more. In that case, the number of pixels determined low-luminance region in addition to the threshold S _low as shown in FIG. 8, when the intermediate image, for example, S _low = 0 to 20 in gamma = 0.8, S _low =
Γ = 1.0 when 21 to 40, γ = 1.2 when S _low is 41 or more
It can be. Next, in step S24 shown in FIG. 7, a gradation maintaining judgment of the low luminance region (shadow region) is performed. This is because, when corrected by the γ value determined as described above, it is determined how much the high-density portion is crushed in the print image by the correction, and the γ correction process is performed according to the determination. This is a process of determining whether to maintain the gradation of the high density area when making the image darker.

First, the frequencies from the luminance value (luminance value 0) at the lower end of the luminance range in the histogram obtained as described above toward the high luminance side and up to a predetermined point (luminance value X) are accumulated. This X is, for example, 1 of the maximum luminance value (luminance value 255).
/ 8 (a luminance value of 32). this
The luminance range up to X is a range in which the gradation curve may be corrected in the gradation curve determination processing described below. In other words, by adjusting the gradation in this range, it is possible to maintain the gradation of the high-density portion in the printed image, prevent color collapse, and obtain an image with good gradation as a whole. . This can be determined empirically or experimentally.

The cumulative frequency up to X obtained as described above is
S ′ is the same as the accumulated frequency obtained in the above-described low-luminance area pixel number determination process. Next, what percentage of the total number of pixels the cumulative frequency S ′ corresponds to is calculated. The ratio of the cumulative frequency to the total number of pixels in this low-luminance area is S _low ′. That is, similarly to the S _low, a S _low '= (low brightness region cumulative frequency S in') / (total number of pixels) (%).

For example, in the case of the image shown in FIG. 5, the area indicated by the dark diagonal lines is an area having the ratio indicated by S _low ′, and is 5% in the fertilizer. As can be seen from this figure, when S _low ′ is small as in this example, even if a tone curve with a small γ value is set and the correction to make the print image darker is made, there are few areas where the color is destroyed. On the other hand, in the example shown in FIG. 6, S _low ′ is 20%. In this example, S _low ′ is a relatively large value. In this case, when a gradation curve with a small γ value is set, a vivid color is obtained from the middle luminance region to the high luminance region. The high-density area of the print image obtained by correcting the low-brightness area occupying% is darkened. Determination of Corrected Tone Curve Based on the value of S _low ′ obtained in the tone maintaining determination process for the low luminance area in step S24, a corrected tone curve determination process is performed in step S25. That is, this processing
Paying attention to S _low ′, it defines a tone curve that can deepen the image without causing collapse of the high density portion of the print image due to the result of the correction of the low luminance area. For each of the γ values obtained in the value determination process, the range in which the gradation of the low luminance region is maintained in the gradation curve and the slope of the straight line are determined based on the value of S _low ′.

In FIG. 9, for example, for the image to be processed, γ = 0.8 in the above-mentioned determination of the correction γ value, and then the value of S _low ′ in the gradation maintaining judgment processing of the low luminance area is For example, if it is determined that S _low ′ = 0 to 5, it is determined that the ratio of the area that is deeply crushed is small even if an attempt is made to increase the density of the entire print image, and the above-described equation using the simply obtained γ value as it is. Is applied. on the other hand,
When the γ value is 0.8 and S _low ′ is 6 or more, when trying to increase the density of the entire print image, it is determined that the proportion of the area of the high-density portion that is densely crushed is large, and the luminance value is 0 to X. The gradation of the pixel is maintained (that is, γ is set to 1 and no correction is performed), and the range from the luminance value X + 1 or more to the maximum luminance value (luminance value 255) is a gradation represented by the same expression as the above expression. Correction is performed using a tonal curve (a curve represented by S _low ′ = 20 in FIG. 9). More specifically, in the example shown in the drawing, Y ′ = Y in the range of 0 ≦ Y ≦ 30, Y ′ = 22 in the range of 31 ≦ Y ≦ 255.
4 × {[(Y-31) / 224] ^{1 / γ} } +31.

The above description relates to the case where the γ value is 0.8.
The threshold value (6 when γ is 0.8 as in the above example) for determination based on the value of S _low ′ can be different for each γ value. However, when the γ value is 1 or more, the correction for increasing the density of the print image is not performed, and therefore, in the present embodiment, the gradation curve is not changed.

In the above embodiment, the brightness value X is constant regardless of the image to be processed. However, the value of X may be changed depending on the histogram. In the example shown in FIG. 9, the correction is not performed (the γ value is 1) in the area of the luminance values 0 to X, but the value of S _low is, for example, 6 to 19
In the case of%, even if the gradation of the low luminance area is slightly crushed and the gradation of the area having the luminance value X or more is widened, for example, the gradient of the straight line of the gradation curve between the luminance values 0 to X is halved. Good.

Further, in the above-described example, as shown in FIG. 9, at the luminance value X, the straight line in the low luminance region and the γ curve in the intermediate luminance region and the high luminance region are simply connected. Needless to say, the gradation can be more continuously expressed by being connected smoothly.

(LUT Creation) When the above-described gradation curve determination processing (step S2 in FIG. 4) is completed, an LUT is created in step S3 shown in FIG. That is, a look-up table (LUT) for luminance correction is created based on the gradation curve indicated by the γ value obtained in the gradation curve determination processing.

The LUT of the present embodiment outputs an output luminance signal obtained by multiplying the reciprocal of the γ value obtained as described above to the ratio of the maximum luminance of each input luminance signal to the maximum luminance value and multiplying the result by the maximum luminance value. In this example, all the brightness values obtained in the correction relationship using the γ value are described corresponding to all the values in the brightness range (brightness values 0 to 255). That is, if the input luminance signal is Y and the output luminance signal is Y ′, LUT L [Y] is Y ′ = 255 ×
It is dynamically created by performing the conversion represented by the equation [(Y / 255) ^{1 / γ} ]. That is, it is created for each processing of the target image. By dynamically creating a correction table in this way, the required memory amount can be reduced.

The LUT may be prepared statically in a memory in advance for each γ value instead of being dynamically created. (Correction) Next, in step S4 shown in FIG. 4, the luminance signal Y is corrected. That is, the L created as described above
By the UT L [Y], the luminance value Y of the input image is represented by Y ′ =
L [Y] and perform luminance correction (B shown in FIG. 3).
2).

Further, the luminance signal Y 'whose luminance has been corrected and the color difference signals Cr and Cb of the input image are returned to the R, G and B signals (the processing of B3 shown in FIG. 3), and the corrected image signal R' Create G'B '.

In the above-described embodiment, the correction regarding the luminance value Y has been described. However, the same correction may be directly performed on each of the R, G, and B signals. At this time, the above L
Using a UT, in the LUT instead of Y, R, G,
The correction can be performed using R ', G', B 'instead of B, Y'.

Since such correction for the R, G, and B signals does not require RGB-YCrCb conversion, the processing speed can be improved.

<Other Embodiments> The present invention, as described above,
The present invention may be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, and the like) or may be applied to an apparatus including one device (for example, a copying machine and a facsimile machine).

FIG. 4 is a block diagram of an apparatus connected to the various devices or a computer in the system for realizing the functions of the above-described embodiment. The present invention also includes a software program code as shown in FIG. 7, which is implemented by operating a computer (CPU or MPU) of the system or apparatus according to a stored program to operate the various devices. It is.

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 stored storage medium 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. Needless to say, the program code is included in the embodiment of the present invention even when the functions of the above-described embodiment are realized in cooperation with application software or the like.

Further, the supplied program code is stored in a memory provided in a function expansion board of the computer or a function expansion unit connected to the computer, and then stored in the function expansion board or the function storage unit based on the 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.

[0072]

As is apparent from the above description, according to the present invention, when the shadow area occupies a large part of the image, the density of the entire image is increased while preventing the collapse of the color of the high density part in the output image. Can be achieved.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a print system according to an embodiment of the present invention.

FIG. 2 is a diagram illustrating processing of a printer driver in the system.

FIG. 3 is a diagram mainly showing a configuration of signal conversion in an automatic gradation correction process performed as an image correction process among the processes of the printer driver.

FIG. 4 is a flowchart illustrating a procedure of the automatic gradation correction process.

FIG. 5 is a diagram illustrating a histogram when an image to be processed by the automatic gradation correction process is a bright image.

FIG. 6 is a diagram illustrating a histogram when an image to be processed by the automatic gradation correction process is a bright image.

FIG. 7 is a flowchart showing a processing procedure for determining a gradation curve in the automatic gradation correction processing shown in FIG.

FIG. 8 is a diagram showing the contents of a table used in the gradation curve determination processing and explaining how to determine a γ value according to the type of image.

FIG. 9 is a diagram illustrating a conversion characteristic curve of a luminance correction table and illustrating a change in a gradation curve for maintaining a gradation in a low luminance region.

[Explanation of symbols]

 REFERENCE SIGNS LIST 100 host computer 101 application 102 $ S (operating system) 103 printer driver 104 monitor driver 105 monitor 106 printer 107 HD 108 CPU 109 RAM 110 ROM 120 image correction processing 121 printer correction processing

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor Kochi Tsuchiya 3-30-2 Shimomaruko, Ota-ku, Tokyo Canon Inc. (72) Inventor Yuji Akiyama 3-30-2 Shimomaruko, Ota-ku, Tokyo Non-corporation F-term (reference) 5B057 CA01 CA08 CA12 CA16 CB01 CB08 CB12 CB16 CE11 CH01 CH07 CH11 DB02 DB06 DB09 DC23 5C077 LL19 MP08 NN02 NP01 PP15 PP32 PP52 PP53 PQ12 PQ19 PQ22 PQ23 TT02 5C079 MA03MA051 AA06 FA37 GA53 MA03

Claims (13)

[Claims] 1. A correction condition for correcting a component related to brightness of the image data is determined based on a histogram corresponding to a component related to brightness of an image indicated by the image data, and the image data is corrected according to the determined correction condition. An image processing method for correcting, comprising: determining, in the histogram, a ratio of a predetermined range of the component in the histogram, and determining the correction condition based on the determined ratio. 2. The step of determining the correction condition includes, when the ratio is equal to or more than a predetermined value, changing the correction of image data in a predetermined range of the component and changing the component value in the determined correction condition. 2. The image processing method according to claim 1, wherein the correction condition is determined so as to perform the correction to be maintained. 3. In the histogram, a component value whose cumulative frequency from a maximum value or a minimum value of the component value indicates a predetermined value in a range of the component value is obtained, and in the histogram, a predetermined component is calculated from the minimum value or the maximum value. Calculating a cumulative frequency up to a value, further comprising the step of: determining the correction condition; determining the brightness level based on the determined component value and the cumulative frequency; and determining the determined brightness level. 2. The image processing method according to claim 1, wherein the correction condition is determined based on the ratio and the ratio. 4. The step of determining the correction condition, wherein, when the ratio is equal to or more than a predetermined value, among the correction conditions determined based on the degree of brightness, a predetermined component value is set from a minimum value of the component value. 4. The image processing method according to claim 3, wherein the correction condition is determined such that the correction of the image data up to and including the component value is maintained. 5. The image according to claim 3, wherein the step of determining the correction condition determines the degree of brightness based on a ratio of the cumulative frequency to the total number of pixels of the histogram. Processing method. 6. The image processing method according to claim 1, wherein the component value is a luminance value indicated by image data. 7. The step of determining the correction condition includes determining the image in a plurality of levels of brightness based on the component values, and determining the correction condition differently for each of the determined plurality of levels of brightness. 7. The method according to claim 3, wherein
The image processing method according to any one of the above. 8. The step of determining the correction condition includes determining a brightness distribution of the image in a plurality of levels for each of the plurality of levels of brightness based on the ratio, and determining the determined brightness distribution of the plurality of levels. The image processing method according to claim 7, wherein the correction condition is determined differently for each image. 9. A method for determining the degree of brightness of the image from a histogram relating to the number of pixels of the value of the component of the image represented by the image data, and correcting the component related to the brightness of the image data based on the determination. An image processing method for determining a degree and correcting the component according to the determined degree of correction, wherein in the histogram, a cumulative frequency from a maximum value or a minimum value of the component value range indicates a predetermined value. Calculating a component value; obtaining a cumulative frequency from the minimum value or the maximum value to a predetermined component value in the histogram; obtaining a cumulative frequency from the minimum value to a predetermined component value in the range of the component value in the histogram. A ratio in the histogram is obtained, and the degree of brightness is determined based on the obtained component value and the cumulative frequency. Image processing method characterized by comprising the step of determining the degree of the correction based on the different the brightness and the ratio. 10. An image for correcting a component related to the brightness of the image data based on a histogram corresponding to a component related to the brightness of the image indicated by the image data, and correcting the image data according to the determined correction condition. A processing device, comprising: a determination unit for obtaining a ratio of a predetermined range of the component in the histogram in the histogram; and a setting unit for determining the correction condition based on the obtained ratio. Image processing device. 11. The method according to claim 1, wherein, when the ratio is equal to or more than a predetermined value, the setting unit changes the correction of a predetermined range of the component among the predetermined correction conditions and performs correction for maintaining the component value. The image processing apparatus according to claim 10, wherein the correction condition is determined. 12. A storage medium for storing a program readable by an information processing device, wherein the program relates to a brightness of the image data based on a histogram corresponding to a component related to a brightness of an image indicated by the image data. An image processing program for determining a correction condition for correcting a component and correcting the image data according to the determined correction condition, wherein in the histogram, a ratio of a predetermined range of the component in the histogram is determined. A storage medium storing an image processing program having a step of determining the correction condition based on a ratio. 13. An image processing method for setting a correction condition for an input image according to a ratio of a shadow region in an input image, wherein the input image is corrected according to a ratio of a first shadow region in the input image. A first correction condition for the first shadow region is set, and the first shadow region is different from the first shadow region in accordance with a ratio of the second shadow region in the input image.
An image processing method comprising: adjusting a correction condition for a shadow area of the correction condition.