JPH0965158A - Picture processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent the generation of noise due to conversion errors by adjusting a contrast after performing conversion from luminance and color difference signals to the respective color components of RGB or the like in the case of separating the luminance signals and the color difference signals and processing pictures in a processor for binarizing color natural pictures by an error propagation method for the respective color components of RGB or the like. SOLUTION: The processor for binarizing the color pictures for the respective color components of RGB or cyan, magenta and yellow, etc., is provided with a means 1 for separating the luminance signals and the color difference signals from color picture signals, the means 3 for converting the luminance and color difference signals to RGB, the means 4 for adjusting the contrast and the means 5 for performing a binarization processing 5 by error propagation. Then, the contrast is adjusted after performing the conversion from the luminance signals and the color difference signals to the respective color components of R, G and B or cyan, magenta and yellow, etc.

Description

Detailed Description of the Invention

[0001]

TECHNICAL FIELD The present invention relates to a color image,
The present invention relates to an image processing device that binarizes each color component such as R, G, B or cyan, magenta, and yellow. In particular, the present invention relates to an image processing apparatus that binarizes a color image for each color of RGB signals by an error diffusion method.

[0002]

2. Description of the Related Art In recent years, with the personalization of office equipment such as personal computers and word processors, there is an increasing demand for color images to be captured and processed by a CCD camera or the like. However, when an image is captured using a CCD camera or the like, unlike a facsimile or a scanner, the light source is not constant, so it is necessary to adjust the brightness of the image and the contrast.

On the other hand, the image captured by the camera is RGB
Cyan, magenta, which are the three primary colors or their complementary colors,
The three primary colors of yellow (hereinafter, CMY) are binarized and displayed or printed. This time,
In order to represent an image as close to the original image as possible, it is sufficient if the gradation can be expressed in a pseudo manner even if binarized.

The dither method and the error diffusion method are well known as the pseudo gradation expression method. In the dither method,
The threshold value is changed for each pixel according to a certain pattern in a predetermined set of several pixels. As a result, the number of dots exceeding the threshold value in the set changes according to the pixel value, so that it looks as if there are gradations.

However, the number of pseudo gradations to be expressed and the resolution cannot be increased at the same time. That is, if the gradation that can be expressed is increased, the overall image becomes blurred. Further, since the sum of pixel values in a certain area is not stored, there is a drawback that a delicate color tone cannot be reproduced. The well-known error diffusion method can solve these problems and obtain a higher-quality binary image than the dither method.

In this binarizing error diffusion method, a threshold value is compared with a pixel value (a value held for each color component such as an RGB signal and luminance in each pixel), and it is judged whether the value is 1 or 0. The difference between the pixel values of the original image is defined as an error, and the difference in the sign of the error is distributed to the unprocessed pixels. As a result, the error is canceled out, and the sum of the pixel values of the original image and the binarized image is preserved in a certain region, so that a high-quality image is obtained as compared with the dither method.

However, there is a drawback that the contour portion is blurred. Therefore, as shown in Japanese Patent Laid-Open No. 3-145273 (H04N1 / 40), it is necessary to enhance the contour in order to improve this. This outline enhancement is R
When applied to each of the GB signals, the circuit scale is increased, and there is a problem that hue shift occurs in the contour portion.
As shown in FIG. 2, the natural color image is separated into a luminance signal and a color difference signal, and these processes are performed only on the luminance signal.

In FIG. 2, reference numeral 1 separates a color TV signal, which is an NTSC signal, into a luminance signal and a color difference signal. Reference numeral 2 is a contour enhancement circuit for enhancing the contour of the luminance signal. Reference numeral 9 is a contrast adjusting circuit for adjusting the contrast of the luminance signal. A conversion circuit 3 converts the luminance signal and the color difference signal into RGB signals.

Reference numeral 5 is a circuit for converting the RGB signal into a binary signal by utilizing an error diffusion process, and is a circuit for converting the RGB signal into a binary pseudo halftone signal.

[0010]

In the image processing apparatus shown in FIG. 2, when edge enhancement and contrast adjustment are performed with a luminance signal and converted into an RGB signal and then binarized by error diffusion, a white background or the like is not displayed. Natural points may appear. An example thereof is shown in FIG.

FIG. 3A shows a time when the image of a person is captured by a CCD camera or the like, processed according to the conventional system of FIG. 2, and the contrast adjustment is completed. The person (62) appears darker than the background (61), and as a result of increasing the contrast, the background is completely white. FIG. 3B shows that the luminance and color difference signals are converted into RGB signals and binarized.

As shown in FIG. 3 (b), an unnatural point (63) appears on the background that should be pure white.
This is because the conversion result (RGB) becomes the upper limit due to the conversion error when converting the saturation and data that exceeds the possible upper limit (255 for 8 bits) into the RGB signal during contrast adjustment. Because the value is slightly smaller than the value.

This will be described with reference to FIG. The data handled here are RGB signals, luminance signals, color difference signals (C
It is assumed that both r and Cb) have 8 bits. That is, each possible value is 0 to 255 (color difference signal is -127 to
128). Here, it is assumed that there is a pixel having a value as shown in FIG. This pixel has a value of only luminance 150, and the color difference signal is set to 0 for simplification of description.

Generally, the image of a CCD camera has a weak contrast. Here, it is assumed that the luminance is doubled in order to increase the contrast. Then, as shown in FIG.
The brightness value exceeds the upper limit value 255. Since the value exceeding 255 cannot be handled, the luminance of the pixel is set to 255 (that is, white).

After this,

[0016]

[Equation 1]

According to the equation (1), the luminance signal and the color difference signal are R
Converted to a GB signal. If this conversion is ideal, the RGB upper limit values will be 255 as shown in FIG.
It will be white after conversion. In this case, there is no problem because the value saturated in the luminance signal has the same value (255) as that when each RGB is saturated even after conversion to RGB.

However, when the conversion matrix of equation (1) for converting the luminance and color difference signals into RGB is realized by hardware, an ideal matrix cannot always be created, so an error occurs in conversion. Due to this conversion error, the converted value may exceed 255 or may be insufficient as shown in FIG.

When each color is binarized by error diffusion, this slightly lacking portion is sequentially accumulated due to the characteristic peculiar to error diffusion, and when the accumulated value exceeds a predetermined value, this color is changed. It will not develop color. For example, a portion where the B signal does not develop color is only RG and therefore appears as a yellow dot. In other words, as a result of the contrast adjustment, a point with color appears at a portion that should be saturated and blown out and become pure white.

The points generated by this conversion error and error diffusion are called conversion error noise. In this conventional example, the contrast adjustment is realized by multiplying the brightness of the pixel and each of the RGB components by a constant, but increasing the contrast means increasing the difference between the maximum value and the minimum value in each pixel. Therefore, even if another method is adopted, the contrast adjustment has a property that each pixel value is easily saturated.

Further, when the contrast is adjusted, since it is performed with reference to a specific portion (for example, a human face) in the image, other portions (background, etc.) tend to be saturated, and conversion error noise often appears.

[0022]

In the present invention, the contrast adjustment in which the pixel value is easily saturated is performed after the conversion of the luminance signal and the color difference signal into the RGB signal.

[0023]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The structure of the present invention will be described with reference to the first embodiment of FIG. Here, the conditions such as the number of bits for each color component are the same as in the conventional description. The input color image is separated into a luminance signal and a color difference signal by the luminance / color difference separation circuit (1).

The contour of the separated luminance signal is emphasized by a contour emphasizing circuit (2). This prevents the enlargement of the circuit size and compensates for the drawback of blurring the contour in error diffusion and dither processing. As a specific example of the edge enhancement, there is a method of calculating the Laplacian of the luminance in the original image and adding it to the original image.

Next, the RGB conversion circuit (3) converts the luminance signal and the color difference signal after the edge enhancement into RGB signals.
This is to finally obtain binary data for each of RGB. The state of the converted values at this time is shown in FIG. Differences due to slight errors due to conversion appear in each of the RGB color components.

Next, the contrast adjustment circuit (4) adjusts the contrast for each of the RGB colors. The contrast adjustment will be described with reference to FIG. Here, in order to increase the contrast, consider the case where the RGB values in each pixel are doubled.

Then, as shown in FIG. 5B, all of RGB are saturated and exceed the upper limit value, and the result after the contrast adjustment is as shown in FIG. 5C. Input data to the error diffusion circuit in the conventional example of FIG. 2 FIGS. 4 (e) and 5 (c)
Comparing these, it can be seen that the same data as in FIG. 4D is input to the error diffusion circuit 5 according to the present embodiment.

Thereafter, the error diffusion circuit (5) performs binarization processing. At this time, the conversion error noise that has appeared in the past does not appear. In this way, the conversion error noise can be prevented by adjusting the contrast after converting the luminance and color difference signals into RGB. A second embodiment of the present invention will be described with reference to FIG.

In the second embodiment, after the color image signal is separated into the luminance signal and the color difference signal by the luminance / color difference separation circuit (1), the black level is adjusted by the black level adjustment circuit (7). . The luminance signal in a color image captured by a CCD camera or the like is 0 even with the smallest value
Since it hardly occurs, the constant value is subtracted from the brightness value of each pixel to adjust the brightness of the black portion to zero. This tightens the screen and improves the contrast.

From the above equation (1), subtracting a constant value from the luminance signal is completely equivalent to subtracting the same value from each of the RGB components. Is effective in reducing After this black level adjustment, processing is carried out by the contour emphasizing circuit (2), and the subsequent steps are the same as in FIG.

In the second embodiment, the black level adjusting circuit (7) is placed before the contour emphasizing circuit (2), but the order of processing may be reversed. A third embodiment of the present invention will be described with reference to FIG. In the first embodiment, the luminance and color difference signals are RG
B signals are converted into RGB signals in the third embodiment.
It is not a signal but a CMY signal.

That is, the YMC conversion circuit (8) for converting into a CMY signal is arranged before the contrast adjustment circuit (4). Generally, RGB is used for display on a display or the like, and CMY signals are used for output to a printer or the like. For the purpose of printing only, the third embodiment is more efficient than the first embodiment of FIG.

Although the luminance and color difference signals are directly converted into CMY signals in this embodiment, they may be converted into RGB signals and then subjected to processing such as contrast adjustment and converted into CMY signals at the time of output. On the contrary, it may be converted into a CMY signal once and then converted into an RGB signal at the time of output. In this case, in addition to the configuration of FIG. 7, a conversion circuit for converting an RGB signal into a CMY signal or a CMY signal into an RGB signal is required.

Regarding printing, K (black) may be added to the three primary colors called CMY signals in this embodiment. In the present embodiment, a CMY signal includes a CMYK signal.

[0035]

INDUSTRIAL APPLICABILITY According to the present invention, a conversion error is generated at the time of conversion into a CMY signal or an RGB signal or the like, and a conversion error, which is a peculiar problem that occurs in an image processing apparatus that binarizes by an error diffusion method, It is to prevent noise. In the present invention, the brightness and color difference signals are converted into RGB and other color components only by a simple circuit change, in which the contrast adjustment in which the pixel value is easily saturated is performed after the conversion from the brightness signal and the color difference signals to the RGB signals and the like. It is possible to prevent deterioration of the image due to conversion error noise at the time of performing, and obtain a high-quality image.

[Brief description of drawings]

FIG. 1 is a diagram showing a first embodiment of the present invention.

FIG. 2 is a configuration example of conventional image processing.

FIG. 3 is a diagram illustrating generation of conversion error noise.

FIG. 4 is a diagram illustrating a cause of conversion error noise generation.

FIG. 5 is a diagram illustrating signal processing according to the present embodiment.

FIG. 6 is a diagram showing a second embodiment of the present invention.

FIG. 7 is a diagram showing a third embodiment of the present invention.

[Explanation of symbols]

(1) ... ・ Luminance signal / color difference signal separation circuit, (2) ・ ・ ・ ・ Contour emphasis circuit, (3) ・ ・ ・ ・ Conversion circuit for converting luminance signal / color difference signal into RGB, (4) ・・ ・ ・ Contrast adjustment circuit (5) ・ ・ ・ Error diffusion processing circuit (6) ・ ・ ・ ・ Image capturing person, (61) ・ ・ ・ Person, (62) ・ ・ ・ Background, (63 ) ... Conversion error noise, (7) ... Black level adjustment circuit, (8) ... Conversion circuit for converting luminance signal and color difference signal into CMY signal.

Claims (2)

[Claims] 1. An image processing means (2) for performing image processing on at least one of a luminance signal and a color difference signal.
And conversion means (3, 8) for converting the luminance signal and the color difference signal including the image-processed signal into signals of respective color components of R, G, B or cyan, magenta, yellow, etc., and the respective color components And a pseudo halftone converting means (5) for binarizing the contrast-adjusted signals of the respective color components by an error diffusion method. Image processing device. 2. The image processing apparatus according to claim 1, wherein the image processing means (2) performs edge enhancement processing of a luminance signal.