JPH0265466A - Picture processor - Google Patents

Abstract

PURPOSE:To express a picture observed preferably by calculating a difference between a maximum value and a minimum value of a data on a different 3-dimension axis, applying masking processing in response to an optional coefficient to discriminate whether or not the result of the calculation is within a prescribed range. CONSTITUTION:The difference between a maximum value and a minimum value of a picture element of a data on a different 3-dimension axis such as an RGB system is calculated by a processor 8 and a mean value is obtained by an integration counter 10. Moreover, a masking processing means 9 applying masking processing is provided in response to an optional coefficient and a CPU 1 gives a command to a parameter controller 3 to discriminate the mean value within a prescribed range and the coefficient of the masking means is varied so that the mean value comes within a prescribed range to apply the masking processing automatically. Thus, the characteristic of the picture is judged automatically to decide the masking coefficient, then the picture observed preferably is outputted easily.

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Field of Application] The present invention relates to an image processing apparatus, and particularly to a color image processing apparatus.

[Conventional technology]

For example, in a color image input/output system using a color scanner and a laser color printer, generally,
Each color input density signal is subjected to gradation processing from a device that separates and reads a color original (for example, a color scanner), and each color output density signal after this gradation processing is input to an image output device (for example, a laser color printer). I try to do that. Then, the final output image (i.e., the directly output image in systems using the above-mentioned laser color printer, etc., or the printed matter printed using a halftone screen in color plate making systems using a color scanner) is made visually appealing. Therefore, correction is generally performed using a gradation conversion table.

In other words, for example, in a color plate making system using a normal color scanner, the scanner input head is manually moved to the above-mentioned specific point on the scanner drum, and the finished halftone percentage of each color (usually yellow magenta and cyan) at that specific point is displayed. If the halftone percentage is different from the desired halftone percentage, move the tone conversion table correction knob to correct the halftone conversion table to the desired halftone percentage. Also, when using a layout scanner, display the manuscript on a graphic display,
The above specific point is indicated using a light bar, joystick, etc., and the rest of the process is to modify the gradation table in the same manner as above.

On the other hand, as a method for automatically correcting the tone table described above, the average value of each RGB (or YMC) of image data is calculated, and the image data is biased (translation of the tone table) so that the average values are the same. There is a way to correct it by applying . In addition, highlight points of image data (image data values with the lowest density value or pixel data values at low density measurements where the number of pixels exceeds a predetermined value) and shadow points (values of image data with the highest density value) pixel data value,
The pixel data value on the high density side where the number of pixels exceeds the predetermined value) is the maximum value of the digital data (255 for 8-bit data) and the minimum value (0 for 8-bit data).
) There is a method to automatically create and modify a tone table so that

[Problem to be solved by the invention] However, these methods convert each image plane of RGB (or YMC) into an image that is pleasing to the eye by converting the tone table (γ conversion). Yes, but I haven't gotten to the point where I can automatically convert the hue. In other words, automatic masking processing is not performed to make the image look more appealing.

SUMMARY OF THE INVENTION An object of the present invention is to provide an image processing device that can express the appearance in a preferable manner.

[Means to solve the problem]

In order to achieve such an object, the present invention provides a means for calculating the difference between the maximum value and minimum value of data on different three-dimensional axes for a desired pixel of a color image, and a means for calculating the calculation result for the desired data. The image processing apparatus is characterized in that it has means for performing masking processing according to an arbitrary coefficient, and determining means for determining whether the result of the calculation is within a predetermined range.

〔Example〕

Before explaining the structure of the embodiment of the present invention, experimental results that form the background of the present invention will be explained below.

As stated in Evans' theorem, the integral value of each RGB data of a normal color image is at a substantially constant statistical level. Such statistical results are applied to the above-mentioned γ transformation and the like. Therefore, the inventor conducted an experiment to see if such a statistical tendency exists for color balance, and whether it is possible to quantitatively determine the parameters that humans find desirable.As a result, the following results were obtained.

It is considered preferable that the average value of the data of the difference between the maximum and minimum values of each pixel between each plane of the RGB digital color image is within a certain range. If it is less than that, the overall color will look faded. In this experiment, we used a photographic image as the input color image, A/D converted the density range from 0 to 2.0 using 8 bits, and judged the data as described above.As a result, the digital count value was 30 to 40. It was determined that the area around . In addition, images other than those described above that are judged to be preferable include scenes in the spotlight at a concert or the like, and poster images consisting mainly of text or illustrations, which are judged to be images under special conditions. The present invention is intended to more preferably express images such as general landscapes, group photographs, portraits, etc. other than those under such special conditions. Here, the digital count value for judgment is 3
The value of 0 to 40 depends on the characteristics of this experimental device (
The spectral filter characteristics of the input device, the sensitivity distribution, the color development characteristics of the output device, etc.) are not limited (it is said that it is preferable if it does not exist within a certain range).

According to a preferred embodiment of the present invention described below, there is provided a means for calculating the difference between the maximum value and the minimum value for each pixel of image data on different three-dimensional axes such as RGB system, and a means for calculating the difference between the maximum value and the minimum value, and a masking processing means for performing masking processing according to an arbitrary coefficient; and a means for determining whether the average value is within a predetermined range; A device is disclosed that automatically performs masking processing by changing coefficients of a masking means,
The present invention provides an image processing device with preferable output image reproduction;
The present invention can be used not only for all devices that output color images such as laser color copying machines, print layout systems, image editing devices, and image data retrieval devices, but also for image input devices that read images. I'm bored.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a schematic configuration diagram as an embodiment of the present invention, in which an image read from a CCD scanner is processed to obtain preferable color reproduction and output to a color laser printer.

In the figure, l is a control processor (CPU),
Controls the entire device. A program memory 2 stores CPU control programs and various data. The parameter controller 3 controls the computing unit 5, parameter memory 4, and parameter setting l according to instructions from the CPUI, etc.
106, and performs initialization, setting, comparison, etc. of parameters necessary for control, which will be described later. Further, a keyboard 24 for inputting various commands and instructions, a CRT controller 25, and a CRT 26 for displaying the contents are connected to the parameter setting l106.

The processor 8 and the CPUI are connected via the CPU bus 2o and the image controller 7.
is the core part of the image processing unit 23, and the image memory 11 . 1
2. 13 and image data l1017, and performs calculation results. The operations here include four arithmetic operations, logical operations, maximum value and minimum value operations, and RGB3 between each brain of the image memory or between arbitrary constants.
You can calculate the difference between the maximum and minimum values of the three RGB data for each pixel, or convert the RGB three-dimensional data to data on other three-dimensional axes (for example, HLS or YIQ).
It also performs calculations to convert to the coordinate system). Then, the result is sent back to any selected image memory 11, 12, 13. The image memory 11 is for storing original image data, the image memory 2 is for outputting a masking processing result image, and the image memory is a memory for work during calculation.

The masking processing means 9 performs masking processing (creating one pixel data by performing four arithmetic operations from three pixels of three branes) using the coefficient α set for three branes such as RGB in the image memory 11, and converts the result into an image. Write to the brain of memory 12.

This will be explained below using FIG.

FIG. 2 shows the configuration of the image memory 11. The size of the image is 512x512, and the image memory consists of three branes. Now, three branes are assigned to RGB.

R(i,j), G(i,j), B(i,j) represent RGB pixel data, and are 8 bits (0 to 2).
55). Let α be the coefficient set in the masking processing means 9, process the R, G, and B branes in FIG. 2, and calculate the results as R' (i, D, G' (
L j), B' (i, j), the following relational expression is obtained.

R' (i, j) = (1,0+2*α) * R(i,
D-α*G(i, j)-α*B(i, j)G' (i,
j)=-α*R(i, D +(1,0+2*α)*G(
i, D-α*B(i, DB' (Lj)=~α*R(i
, j)-α*G(i,j)+(1,0+2*α)*B(
ij) (However, 1 < = i, j < = 5121 The integration counter lO calculates the sum of the pixel data values of the selected brane in the image memory 11, 12, 13. In other words, for the R-brane in Fig. 2, ΣR (i, D will be found. Using the results, the average value ΣR(i, j) /N (where N is the total number of pixels) of the image data will be found.

FIG. 4 shows the state of a data table of coefficients for incrementing and decrementing the masking coefficient α to be set in the masking processing means 9. This coefficient means that it differs depending on the dynamic range setting value of the input device.

That is, here, ΔαO indicates the case where the concentration range is input from 0 to 2.0, and Δα1 indicates the case where the concentration range is input from O to 2.5.
In this case, Δα2 is a concentration range of 0 to 3.
The case where 0 is input is shown. i.e. a table addressed by the concentration range of the input device,
It is stored in the parameter memory 4.

The image data l1017 is an interface unit for image data input and output devices, to which image input/output devices such as a CCD scanner 27 and a color laser printer 28 are connected, and these image input/output devices can be selectively operated according to CPU commands. It's working. The color laser printer 28 itself is also equipped with a masking processing circuit for correcting its own coloring characteristics with respect to digital input data.

Image memory 11. 12. Each of 13 has a frame configuration of 3 channels (for example, RGB or HLS), and is connected to both the CPU bus 20 and the video bus 21, so it is possible to read and write from the CPU to any of the image memories 11, 12, and 13. , it is also possible to use the processor 8 to perform calculations on image data between arbitrary memories.

High-speed RAMs constituting lookup tables 14, 15.16 are connected to the video bus 22 side of the image memories 11, 12.13, respectively, and each frame memory of these lookup tables has a capacity of 256.
*Has an 8-bit address space. Furthermore, the eight address lines of each frame memory of each lookup table are directly connected to the 8-bit (256 grayscale) output from the corresponding image memory, and the data line of each lookup table is connected to the video bus 22. ing. The CPU, via the image memory controller 7 and processor 8, reads these lookup tables 14.
You can freely read and write the contents of 15°16.

The graphic controller 18 is a controller section of the graphic display CRT 19 that displays input images, and controls the image memory 11 . 1
2. The contents of the lockup tables 14.13 are selectively switched, and the contents of the lockup tables 14. 15. The digital image signal output from 16 is converted into an analog video signal and displayed in color on an image display graphic CRT+9.

The CRT 26 is used to display parameter setting contents and parameter setting requests to give instructions to the operator.

[Description of Processing Operation] FIG. 3 shows a flowchart showing the operation of a preferred color reproduction process of the embodiment.

The explanation will be given below according to the flowchart shown in FIG.

First, in step Sl, the image data l1017 is switched to the input device selection mode by the function of the CPUI, and the setting conditions of the image input device for inputting the original image data are input.

This displays the dynamic range selection conditions of the CCD scanner 27 on the CRT 26 and requests the operator to set them. Dynamic range refers to the range from where the density of the original must be zero to obtain 8-bit data as the final result.
In this embodiment, there are three types of document density: 0 to 2.0, 0 to 2.5, and 0 to 3.0.

The CPU displays the density conditions on the CRT 26 and requests selection. The operator selects the condition using the keyboard. The selection result is the parameter N0UDO
is stored in the parameter memory 4 as a value of 0 or 12.

Once the image data input conditions are determined in this way, the CPU
gives an instruction to the image processing processor 8, and
/Ol 7 informs the CCD scanner 27 of the setting conditions, reads the original image data according to the conditions,
The image is divided into an R component, a G component, and a B component and stored in the image memory 11.

In step S2, the masking coefficient α is initialized to O by the action of the CPUI.

In step S3, the masking coefficient determined in the previous step is set in the masking processing means 9.

In step S4, masking processing is performed by the masking processing means 9. First, image data is read from the R-brane, G-plane, and B-brane of the image memory 11 and input to the masking processing means 9, and after processing, the result is output to the image memory 12.

Here, the following processing is performed.

First, as R-plane masking processing, (1,0+
2*α) *R(i,D-α*G(i,j)-α*B
(ij) and the result is stored in the image memory 12.
output to the a-brane of Next, as a G-brane masking process, α*R(i, D + (1,0+2*α)*G(i, j)
-α*B(i, j) is calculated and the result is output to the b-brane of the image memory 12. Then, as masking processing for the B plane, α*R(i, j)−α*G(i, j) + (1,0+
2*α)*B(i, j) is calculated and the result is output to the C-brane of the image memory 12.

In the above calculation, if the calculation result overflows (exceeds 255), it is set to 255, and if the calculation result underflows (negative value), it is set to 0.

Further, in this step, the next time the masking coefficient α is initialized, α=0, so the contents of the image memory 11 are simply copied to the image memory 12.

In step S5, the maximum value of each brane (RGB) of the image data stored in the image memory 12 is calculated for each pixel. First, the image data of the C-brane of the image memory 12, which is R-brane data of the image memory 12, and the b-brane data of the image brain 12, which is C-plane data, are read into the processor 8, and the maximum value of each pixel is calculated, and the result is stored in the image memory. Store it in the C-brane of 13. Next, the C-brane data of the image memory 13, which is the resulting image data, and the image memory 1
The processor 8 calculates the maximum value for each pixel with the C-brane, which is the B-data-brane of No. 2, and stores the result in the b-plane of the image memory 13. As a result, image data consisting of the maximum value of each pixel of the three image data of the image memory 12 is written in the b-brane of the image memory 13.

In step S6, the minimum value of each brane (RGB) of the image data stored in the image memory 12 is calculated for each pixel. First, the image data of the C-brane of the image memory 12, which is R-brane data of the image memory 12, and the b-brane data of the image memory 12, which is C-plane data, are read into the processor 8, and the minimum value of each pixel is determined, and the result is stored in the image memory. Store it in the C-brane of 13. Next, the resulting image data, the C-brane data in the image memory 13, and the image memory 12
The processor 8 calculates the minimum value for each pixel between the C-brane, which is the B-data brane, and stores the result in the C-brane of the image memory 13. As a result, image data consisting of the minimum value of each pixel of the three image data of the image memory 12 is written into the C-brane of the image memory 13.

In step S7, the difference between the b-plane data of the image memory 13 obtained in step S5 and the C-plane data of the image memory 13 obtained in step S6 is calculated to determine the maximum value and minimum value of each pixel in the image memory 13. Find the difference data. The processor 8 calculates (b-brane data) - (C-brane data) in the image memory 13, and the result is stored in the C-brane data in the image memory 13.
Write to Brain.

In step S8, the average value of the C-branes in the image memory 13 is calculated and the result is stored in the variable HEIKIN. C.P.
In response to a command from the UI, the integration counter 10 via the image controller 7 calculates the total sum (ΣX (i, D, where X (i,
D is an 8-bit data value, i and j are 1 to 512), and the sum result is calculated as the total number of pixels in the image N (512*512
) to find the average value (variable HEIKIN). The average value HEIKIN is obtained as an integer value rounded down to the decimal point. That is, the variable HEIKIN takes a value from 0 to 255.

In step S9, the variable HEIKIN is compared with a predetermined value (SETTEI 1). Variable HEIKI
If N is greater than the comparison value 5ETTEI1, the process proceeds to step 13. The comparison value 5ETTEI is considered to be because it is a color character or illustration image, and it is determined that preferable color reproduction is not required like a natural image, and the image is output as is without masking processing. The comparison value is stored in the parameter memory 4 in advance.

In step SIO, the variable HEIKIN is compared with a predetermined value (SETTEI 2). variable HEIK
When IN is smaller than the comparison value 5ETTEI2, the process proceeds to step 13. The comparison value 5ETTEI 1 is thought to be due to the image being a black and white image or an image with extremely little color, and it is determined that preferable color reproduction like a natural image is not required, and the image is output as is without masking processing. .

If colors are emphasized through masking processing of such an image (monochrome image), the effects of color shift on the input device will be further amplified, resulting in an image that is not pleasing to the eye. Further, the comparison value is stored in advance in the parameter memory 14 in the same manner as described above.

Step Sll Step S12 is the variable HEIKI
It is a judgment means for setting N to a predetermined range,
The comparison value 5ETTEI 3 is the upper limit setting value, and 5ETTEI 3 is the upper limit setting value.
TEI4 is a lower limit setting value. In step Sll,
Comparison value 5ETTEI If not greater than 3, α=α+
The values of Δα and α are incremented and the process returns to step S3.

Here, Δα is calculated by reading out the corresponding comparison setting value from the parameter memory 4 using the variable N0UDO indicating the state of the dynamic range of the input device.

If the comparison value 5ETTEI3 is greater than 3, the process advances to step S12. In step S12, the comparison value 5ET
If it is larger than TEI4, the value of α is decremented by α=α−Δα and the process returns to step S3. In the same manner as described above, Δα is calculated by reading out the corresponding comparison setting value from the parameter memory 4 using the variable N0UDO indicating the state of the dynamic range of the input device.

Also, if the comparison value is not greater than 5ETTEI 4,
Proceed to step S13.

In step S13, the image data 11017 is switched to the input device selection mode, and the data subjected to image processing in the above steps is output to the color laser printer 28 via the image data 11017. The data in the image memory 12 is set to 11017 for image data as specified by the CPUI.
The image is transferred to the color laser printer 28 via the . After the transfer is completed, an image output command is issued to the color printer 28, and the output is completed.

In this embodiment, the means for calculating the average value, the means for generating addresses, and the means for setting each parameter have been explained based on software sequences using a microcomputer, but by using a dedicated hardware configuration, Needless to say, the same effect can be obtained.

In the above example, the masking coefficient was actually calculated by incrementing and decrementing so that the average value of the difference between the maximum value and the minimum value of each pixel was determined within a predetermined range. For example, similar effects can be obtained by using any known method.

Further, in this embodiment, the process has been described using only the masking process for preferable output image reproduction, but the process using the γ conversion, which is a conventional technique, may also be used in combination. In the previous embodiment, a masking coefficient table (Δα0.Δαl, Δα2) based on the dynamic range difference of the input device was prepared, and the increase/decrease (Δα) of the masking coefficient was determined based on this value.
was selected, but by using the following method, only one coefficient is required.

That is, the variable Δα is set to a value corresponding to the concentration. For example, specifically, the average value of the difference data between the maximum and minimum values in pixel units in the previous embodiment is further divided by the density value of the dynamic range (2, 0, 2, 5, 3, 0), and the value is Set the masking factor with a proportional integer value. Naturally, the value of Δα in the parameter memory must also correspond to the value obtained by dividing the average count value by the density value.

As explained above, according to this embodiment, since the characteristics of the image can be automatically determined and the masking coefficients determined without changing the masking coefficients by the operator, it is possible to easily output an image suitable for viewing. .

This embodiment not only easily solves the problem of color tones being emphasized more than necessary when reversing and outputting an image from a negative film, but also automatically converts faded original images. Fading correction can be performed.

〔Effect of the invention〕

As explained above, according to the present invention, it is possible to preferably express the appearance of a given image.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing a schematic configuration diagram of a preferable image processing device for color reproduction according to this embodiment. FIG. 2 is a diagram showing the state of the image memory and is a diagram for explaining the calculation method. FIG. FIG. 4 is a flowchart explaining the operation of the example, and FIG. 4 is a diagram showing the data structure of the parameter memory. In the figure, l... CPU, 2... program memory, 3
...Parameter controller, 4...Parameter memory, 5...Arithmetic unit, 6...I10 for parameter setting
．． 7... Image controller, 8... Processor, 9... Masking processing means, 10... Integration counter, 11. 12. 13... Image memory, 1
4. 15. 16... Lookup table, 17
...Image data I10.18...Graphic controller, 19...Graphic CRT, 20...
・CPU bus, 21.22...Video bus, 23...
・Image processing unit, 24...Keyboard, 25...CR
T controller, 26...CT, 27...CCD
Scanner, 28...color laser printer. Faith 4 - Diagram

Claims (1)

[Claims] (1) Means for calculating the difference between the maximum and minimum values of data on different three-dimensional axes for a desired pixel of a color image, means for calculating the calculation result on the desired data, and an arbitrary coefficient. An image processing apparatus comprising: means for performing masking processing in accordance with the calculation; and determining means for determining whether the result of the calculation is within a predetermined range.