JP2929983B2 - Color image processing equipment - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a technique for correcting the white balance of a plurality of input images in a digital image processing apparatus so as to unify the disparate color tones to improve the quality of the images.

[0002]

2. Description of the Related Art Conventionally, in this type of image processing apparatus, in order to correct the white balance of an image, a pixel value is manually corrected one by one, and an operator interactively corrects the pixel value. However, for a single image, see JP-A-62-2810.
Some devices, such as the 70 device, automatically correct based on the maximum luminance value in an image. Referring to FIG.
An example of a conventional image processing apparatus will be described based on -281070.

[0003] An embodiment of a conventional device is an image memory 10.
0, maximum luminance value extraction unit 101, correction amount calculation unit 102, correction ROM 103, correction ROM 104, masking circuit 1
It consists of 05.

[0004] From the input Y, RY, and GY signals,
The maximum luminance value in the image,
Alternatively, an average value Ymax of ten points with high luminance is obtained. At the same time, the correction amount calculation unit 102 obtains the color components, RY, and GY of the pixel having the maximum luminance value Ymax as ΔRY and ΔGY, respectively. When Ymax is the luminance average, ΔRY and ΔGY also average, respectively.

The RY and GY signals are converted from the correction amounts thus obtained using the following equation.

(R−Y) ′ = (R−Y) ΔRY × Y / Ymax (G−Y) ′ = (G−Y) ΔGY × Y / Ymax (1) The obtained y, (R−Y) ', (GY)' signal,
The image is converted into a color such as CMY and output.

[0007]

The conventional image processing apparatus has a problem that a plurality of images cannot be subjected to integrated color correction or white balance correction.

In the conventional image processing apparatus, video signals Y, RY, and GY are used as input signals. For example, in a digital image processing on a personal computer, RGB signals are used. Many, Y, R-
Overflow (exceeding the dynamic range of RGB) often occurs in the process of converting the Y, G-Y signals to RGB, and the color may become unnatural when displayed on a monitor or the like.

In the conventional image processing apparatus, since color conversion is performed based only on information of a portion having a high luminance, the quality of a portion having a low luminance cannot be improved.

[0010]

SUMMARY OF THE INVENTION Color image processing of the present invention
The apparatus includes a multi-input image memory for storing a plurality of input images.
A plurality of output image memories for holding a plurality of output images;
Color correction processing is performed on all image data.
And an input image holding input image data
Buffer and RGB values of white pixel and black pixel from image
Specify white and black extraction means to extract and target area to extract
And a reference white bag that holds the reference white.
And a reference black buffer for holding the reference black, and a color change
Create a lookup table for conversion
And table conversion for each of RGB
U, RGB lookup table conversion means and after color conversion
And an output image buffer for holding the
The white and black extracting means extracts the luminance value from the RGB value.
Take a luminance histogram to calculate the luminance value extraction means
Histogram calculation means and the maximum brightness from the histogram
The maximum luminance extraction means to obtain and the minimum luminance from the histogram
The minimum luminance extraction means to obtain and the RGB of the pixel having the maximum luminance
Maximum luminance RGB value to obtain the value as RGB value of white pixel
Calculating means for calculating the RGB value of the pixel having the minimum luminance to a black pixel
And a minimum luminance RGB value calculating means for calculating the RGB value of the minimum brightness .

[0011]

The operation of the image processing apparatus according to the present invention will be described.

The processing contents of the present invention will be described with reference to the flowcharts of FIGS. In this method, a plurality of images to be processed are white-corrected in an integrated manner.

The operator first specifies a reference white value and a reference black value, and the system stores them (step S1). A plurality of image data to be white-corrected are held, and images are input one by one to the buffer (step S2), and color correction is performed by performing the following white correction processing (steps S3 to S5). When the process is completed for one image, the white correction process is sequentially performed on the remaining images by the determination process (step S6). In this way, the process ends after all the plurality of images to be processed are processed. In the white correction process, first, white and black RGB values are extracted from input image data (step S3). A method of extracting white and black RGB values will be described with reference to FIG.

First, a low-pass filter is applied to image data (step A1). An example of a low-pass filter is a local average filter that employs the average value of nearby pixels as a new pixel value.

The pixel value at the position i, j is represented by I (i,
j), when a 3 × 3 local average filter is applied, the output I ′ (i, j) is I ′ (i, j) = (I (i−1, j−1) + I ( i, j-1) + I (i + 1, j-1) + I (i-1, j) + I (i, j) + I (i + 1, j) + I (i-1, j + 1) + I (i, j + 1) + I ( i + 1, j + 1)) / 9 (2) If there are three pixel values like RGB,
A local average filter may be applied to each of R, G, and B. The purpose of the low-pass filtering step (step A1) is to reduce noise, but this step A1 is deleted when performing high-speed processing. Next, a histogram of the luminance of the image is created (step A3). The luminance referred to here indicates a value indicating the brightness of the RGB pixel by a numerical value.
As a method of obtaining a luminance value from an RGB value, CIE-XY
There is a method using the Y value of the Z value. Assuming that the RGB values are NTSC signals, Y can be obtained as follows: Y = 0.299 × R + 0.587 × G + 0.114 × B (3) In addition, the average value of R, G, B,
Alternatively, the maximum value of R, G, B or the like can be adopted as the luminance (brightness) Y of the pixel. Histogram 5
In order to obtain 0, the image data is scanned from the end, and when the value is the luminance Y, the value of the array hist [Y] may be incremented. Further, in order to shorten the processing time, instead of searching for all pixels, pixels can be thinned out and searched every few pixels (step A2) to create a histogram.

The maximum luminance pixel RGB value (Rma) in the image
x, Gmax, Bmax) (step A4), and subsequently, the minimum luminance pixel RGB value (Rmin, Gmi) in the image.
n, Bmin) (step A5). Referring to the histogram 50 of FIG. 5, the maximum luminance value and the minimum pixel in the image can be extracted. Brightness maximum value Ymax51
Is obtained, the maximum luminance pixel RGB value can be obtained as an RGB value when the luminance is Ymax51 by scanning the image again. Similarly, if the minimum luminance value Ymin53 is obtained, the minimum luminance pixel RGB value is determined by scanning the image again to obtain the luminance Ymi.
It can be obtained as an RGB value at the time of n53.

When determining the maximum luminance pixel RGB value,
The number of pixels of α% (α = 0 to about 0.1) of the total number of pixels is Na
Then, the Na-th high luminance pixel can be obtained as the maximum luminance value in consideration of noise. At this time, the luminance value Yma lower than the histogram 50 by the number of pixels of α%
x'52 is used as the maximum luminance value. Then, by scanning the image again and averaging the RGB values of the pixels of Ymax'52 or more, the maximum luminance pixel RGB value can be determined. When determining the minimum luminance pixel RGB value,
First, assuming that the number of pixels of β% (β = 0 to about 0.1) of the total number of pixels is Nb, the Nb-th low luminance pixel can be obtained as the minimum luminance value in consideration of noise. At this time,
A luminance value Y higher by the number of pixels of β% from the histogram 50
min'54 is used as the minimum luminance value. Then, by scanning the image again and averaging the RGB values of the pixels of Ymin'54 or less, the minimum luminance pixel RGB value can be determined.

The maximum luminance pixel RGB value thus obtained is defined as a white RGB value (Rw, Gw, Bw), and the minimum luminance pixel RGB value is defined as a black RGB value (Rb, Gb, B).
b). As the black RGB values, R, G, and B can be stored with the same value. As an example in which R, G, and B are the same, the maximum value of the minimum luminance pixel RGB value (Rmin, Gmin, Bmin) is represented by Rb,
There is a method adopted as Gb and Bb.

Rb = Gb = Bb = MAX (Rmin, Gmin, Bmin) (4) Next, a conversion LUT (lookup table) is created based on the reference white and the reference black (step S4). FIG.
FIG. 1 shows an example of a method of creating an LUT. The reference white 60 and the reference black 61 are provided in advance by the user. Reference white 60, reference black 61, and white RG obtained from the image
Using the B value 62 and the black RGB value 63, the R conversion characteristic 6
4. The G conversion characteristic 65 and the B conversion characteristic 66 are obtained. Using the R conversion characteristic 64 as an example, an example of how to obtain it is shown in equation (5).

R ′ = a × R + ba a = (Rw−Rb) / (Rw0−Rb0) (5) b = Rb0−a × Rb Next, each conversion characteristic of RGB is stored as a lookup table (LUT). . Examples of LUTs for handling 8-bit pixel values include LUT67, LUT68, and LUT.
Shown at 69.

Finally, the whiteness correction processing is completed by converting the pixel values of all the pixels using the created RGB LUTs (step S5).

[0023]

DESCRIPTION OF THE PREFERRED EMBODIMENTS A color image processing apparatus according to an embodiment of the present invention will be described below with reference to the drawings.

FIGS. 1 and 2 are block diagrams showing an embodiment of the color image processing apparatus of the present invention.

In the embodiment of the present invention, a plurality of input image memories 14 for holding a plurality of input images, a plurality of output image memories 16 for holding a plurality of output images, and color correction processing is performed on all image data. 18 to control
And color correction means 19. The color correction means 19 includes an input image buffer 1 for holding input image data.
A white / black extracting unit 2 for extracting RGB values of white and black pixels from an image; a reference white buffer 7 for holding a reference white; and a reference black buffer 8 for holding a reference black
And R for creating a lookup table for color conversion
It comprises a GB table creating means 9, an RGB table converting means 20 for performing table conversion for each of RGB, and an output image buffer 12 for holding image data after color conversion.

Further, the white / black extracting means 2 includes a luminance value extracting means 35 for calculating a luminance value from the RGB values, a pixel thinning search means 43 for thinning out pixel values and searching for a histogram, and a histogram of image luminance. , A maximum luminance extracting means 36 for obtaining the maximum luminance from the histogram, and a minimum luminance extracting means 37 for obtaining the minimum luminance from the histogram.

A plurality of image data input from an image input device 13 such as a scanner is stored in a multiple input image memory 14. Multiple input image memory 1
Data is input to the color correction means 19 one by one from 4 and processed.

In the color correcting means 19, the input image buffer 1
The white RGB value and the black RGB value are acquired by the white / black extracting means 2 based on the image data input to the RGB table creating means 3 and input to the RGB table creating means 3.

In the white / black extracting means 2, the data of the input image buffer 1 is temporarily stored in the image data buffer 32, and the histogram of the luminance value is calculated by the histogram calculating means.

The histogram calculating means 34 is connected to a luminance value calculating means 35 for calculating a luminance value from RGB.

Before calculating the histogram, a noise component is removed from the contents of the image data buffer 32 by a low-pass filter 33, and the image data buffer 32
By writing the data back to the memory, the noise can be removed.

Furthermore, when calculating the histogram, it is also possible to use the pixel thinning-out search means 43 to search the image while obtaining pixel values every several pixels, instead of searching the entire image, and create a histogram. .

The luminance value Ymax of the pixel having the maximum luminance in the image is extracted by the maximum luminance extracting means 36 from the histogram obtained by the histogram calculating means 34.

As described in the section of the means for solving the problem, instead of the maximum luminance extracting means 36, the corrected maximum luminance extracting means 44 reduces the number of pixels of α% of all pixels to Na.
Then, the brightness value of the pixel having the Nath largest brightness value can be adopted and output.

Similarly, the luminance value Ymin of the pixel having the minimum luminance in the image is extracted by the minimum luminance extracting means 37 from the histogram obtained by the histogram calculating means 34.

Further, as described in the section of the means for solving the problems, the corrected minimum luminance extracting means 45 replaces the minimum luminance extracting means 37 with the number of pixels of β% of all the pixels being Nb.
Then, the luminance value of the pixel having the Nb-th smallest luminance value can be adopted and output.

Based on Ymax, the maximum luminance pixel RGB value calculation means 38 is used to calculate and output a white RGB value. The maximum luminance pixel RGB value calculation means 38 performs a process of scanning data in the image data buffer 32 and calculating an average of RGB values of pixels equal to or more than Ymax.

Based on Ymin, black RGB values are calculated and output using the minimum luminance pixel RGB value calculating means 39. The minimum luminance pixel RGB value calculating unit 39 performs a process of scanning data in the image data buffer 32 and calculating an average of RGB values of pixels equal to or smaller than Ymin.

Finally, the black value correcting means 42 performs a process for setting the RGB values of the black value to the same value,
Output the value. As an example of the black value correcting means 42, there is a device for realizing the expression (4) in the term of means for solving the problem. In advance, by reference white black designation means 15,
The reference white buffer 7 holds reference white RGB values, and the reference black buffer 8 holds reference black RGB values.

The RGB table creating means 3 creates the look-up tables of the respective RGB based on the output values of the white and black extracting means 2 and the values of the reference white buffer 7 and the reference black buffer 8, and RLUT4, GLUT5, BLUT6
To hold.

The RGB table conversion means 20 uses the RLUT
4. Based on the data of the GLUT 5 and the BLUT 6, the pixel values of the input image buffer 1 are converted into a table and output to the output image buffer 12. Processing data is stored in the output image buffer 12
Are output to the multiple output image memory 16 and held there, but after one image data is processed, the CPU 18
To check whether or not an unprocessed image remains in the multiple input image memory 14. If there is unprocessed data, the data is input to the color correction unit 19. After all the data of the multiple input image memory 14 has been processed in this way, the result of the multiple output image memory 16 is output to the image output device 17 such as a hard disk or a monitor.

[0042]

As described above, the color image processing apparatus according to the present invention has an effect that it is possible to correct the color balance of a combined and displayed image by simultaneously processing a plurality of image data. is there.

Further, since the color correction can be performed without converting the RGB image data into another color coordinate system, there is an effect that high-speed processing can be performed.

Further, by correcting not only the point having a high luminance (white point) but also the point having a low luminance (black point), there is an effect that the output image quality is improved as compared with the related art.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an embodiment of a color image processing apparatus according to the present invention.

FIG. 2 is a block diagram showing an embodiment of the color image processing apparatus of the present invention.

FIG. 3 is a flowchart illustrating the operation of the present invention.

FIG. 4 is a flowchart illustrating the operation of the present invention.

FIG. 5 is an explanatory diagram of maximum luminance and minimum luminance extraction.

FIG. 6 is an explanatory diagram of a lookup table.

FIG. 7 is a block diagram showing an embodiment of a conventional color image processing apparatus.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Input image buffer 2 White-black extraction means 3 RGB table creation means 4 RLUT 5 GLUT 6 BLUT 7 Reference white buffer 8 Reference black buffer 9 LUT conversion means 10 LUT conversion means 11 LUT conversion means 12 Output image buffer 13 Image input device 14 Multiple Input image memory 15 Reference white / black designation unit 16 Multiple output image memory 17 Image output device 18 CPU 19 Color correction unit 20 RGB table conversion unit 30 White / black extraction unit 31 Input RGB image data 32 Image data buffer 33 Low pass filter 34 Histogram Calculation means 35 brightness value extraction means 36 maximum brightness value extraction means 37 minimum brightness value extraction means 38 maximum brightness pixel RGB value calculation means 39 minimum brightness pixel RGB value calculation means 40 white RGB value 41 black RGB value 42 black Value correction means 43 Pixel thinning search means 44 Correction maximum luminance value extraction means 45 Correction minimum luminance value extraction means 50 Histogram 51 Maximum luminance value Ymax 52 Correction maximum luminance value Ymax '53 Minimum luminance value 54 Correction minimum luminance value Ymin' 60 Reference white 61 Reference black 62 White RGB value 63 Black RGB value 64 R conversion characteristic 65 G conversion characteristic 66 B conversion characteristic 67 R lookup table 68 G lookup table 69 B lookup table 100 Image memory 101 Maximum luminance value extraction unit 102 Correction amount Calculation unit 103 Correction ROM 104 Correction ROM 105 Masking circuit

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-60-87594 (JP, A) JP-A-60-87595 (JP, A) JP-A-5-342344 (JP, A) JP-A-6-87544 178111 (JP, A) JP-A-62-111570 (JP, A) JP-A-62-281070 (JP, A) JP-A-1-221247 (JP, A) JP-A-2-157758 (JP, A) JP-A-4-248681 (JP, A) JP-A-4-257082 (JP, A) JP-A-6-245063 (JP, A) JP-A-7-121681 (JP, A) (58) Fields investigated (Int.Cl. ⁶ , DB name) G06T 5/00 G06T 1/00 H04N 1/60

Claims (6)

(57) [Claims] 1. An input image buffer for holding input image data.
Histogram and a histogram for calculating the luminance histogram from the image
RAM calculation means, and RGB of white pixels and black pixels from an image
White-black extraction means to extract the value and hold the reference white
A reference white buffer and a reference black buffer that holds the reference black.
And a lookup table for color conversion
RGB table creation means for each of RGB
RGB table conversion means for performing table conversion, and color conversion
And an output image buffer for holding the subsequent image data.
Cage, in a white black extraction means calculates a luminance value from the RGB values
Luminance value extracting means, and hiss for taking a luminance histogram.
Obtain maximum brightness from histogram and histogram calculation means
Maximum luminance extraction means and obtain minimum luminance from histogram
The minimum luminance extracting means and the RGB value of the pixel having the maximum luminance
Calculation of maximum luminance RGB value obtained as RGB value of white pixel
Means and the RGB value of the pixel having the minimum luminance
A color image processing apparatus comprising: a minimum luminance RGB value calculating unit that obtains a RGB value . 2. A multi-input image method for storing a plurality of input images.
Memory and multiple output image memory to hold multiple output images
And color correction processing is performed on all image data
Control means for controlling the
The color image processing apparatus according to claim 1. 3. The R, G, and B values of minimum luminance RGB values are set to the same value.
Black value correcting means for correcting the color value to a black value.
3. The color image according to claim 1, wherein the color image is obtained.
Processing equipment. 4. When calculating a luminance histogram, several pixels are used.
Pixel decimation search means for controlling the search every other
The power supply according to claim 1, 2, or 3, wherein
Image processing device. 5. A method for extracting a maximum luminance value from a histogram.
Let Na be the number of α% of the number of pixels instead of the high luminance extraction means.
Then, the luminance value of the Nath pixel is obtained from the higher luminance.
Correction maximum brightness extraction means, and
Instead of the minimum brightness extraction means for extracting the brightness value, Nb
When the number of beta% number, more or al Nb th low luminance
A corrected minimum luminance extracting unit for obtaining a luminance value of the pixel, wherein the maximum luminance RGB value calculating unit is equal to or more than the corrected maximum luminance value
The average value of the RGB values of the pixel group is defined as the RGB value of the white pixel.
The minimum luminance RGB value calculation means calculates the corrected minimum luminance.
The average value of the RGB values of the pixel group having a degree value or less is calculated as
3. The method according to claim 1, wherein the value is obtained as a B value.
Is a color image processing apparatus according to 4. 6. A method for removing noise from image data to obtain a luminance hysteresis.
Low-frequency filtration filter
5. The apparatus according to claim 1, further comprising a data processor.
Or the color image processing apparatus according to 5.