JP2698296B2 - Image processing circuit - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing circuit for improving the contrast of an input image and outputting the image.

[0002]

2. Description of the Related Art Heretofore, there has been a color video printer capable of printing a reproduced video signal from a video device such as a camera-integrated VTR or a laser disk player, or a video signal transmitted by TV broadcasting as an image directly on photographic paper. Is being developed.

[0003] When a desired subject is photographed by a camera-integrated VTR, an automatic adjustment function for exposure, focus, white balance, and the like works, but the nature of the image composed of the subject to be photographed and the background varies. Therefore, it is actually difficult to realize the optimum adjustment state. Therefore, when the image pickup signal from such a camera-integrated VTR is directly supplied to a video printer to print an image, an image having a sufficient contrast may not be obtained.

To improve the contrast of an input image, a technique called histogram conversion has been proposed (for example, "Image Engineering Handbook" edited by Kenji Hiwatari, Asakura Shoten, p. 215). In this method, a frequency distribution of image data forming a screen is checked in advance, and data conversion is performed so that the histogram has an appropriate distribution.

[0005]

The histogram conversion method is an extremely effective method for improving the contrast when the properties of the image to be processed are known in advance. If the images to be processed are different, such as images, the nature of the images is unknown, and the desired effect may not be obtained with a uniform data conversion method.

In general, contrast is improved by performing data conversion so that dark areas in an image are darker and bright areas are brighter. However, in the case of a color image, an image area having the same luminance is used. Even so, if similar conversion processing is performed on regions having different saturations, for example, dark navy blue is converted to black or light blue is converted to white, which causes a problem of so-called “color blur”.

An object of the present invention is to provide an image processing circuit in which appropriate data conversion is performed in accordance with the characteristics of an input image to be processed and the contrast can be improved without lowering the image quality. is there.

[0008]

An image processing circuit according to the present invention comprises first to third detecting means for detecting the characteristics of an input image, and data conversion for performing data conversion on input image data and outputting the result. Means for correcting the data conversion method according to the nature of the image.

The first detecting means includes luminance data representing luminance for each unit area constituting the input image, luminance change data representing the degree of luminance change over the entire input image, a high luminance portion and a low luminance portion in the input image. Chroma data representing the chroma of the luminance portion is detected. The second detecting means detects a main subject area in the input image. Further, the third detecting means includes a first representative value MX and a second representative value MN which are the maximum value and the minimum value of the luminance data for the entire input screen.
And a third representative value MXO and a fourth representative value MNO which are the maximum value and the minimum value of the luminance data in the main subject area.

The data conversion means is for subjecting the input image data to data conversion processing according to a predetermined data conversion method representing the relationship between the input image data and the output image data, and outputting the data. The correction means includes a first representative value MX and a third representative value MX.
For the representative value MXO, the change amounts ΔMX and ΔMX respectively
O, husband for the second representative value MN and fourth representative value MNO
The input / output relationship of the image data is corrected by giving the amounts of change ΔMN and ΔMNO, and the amounts of change ΔMX and ΔM are adjusted so as to satisfy at least the following three conditions.
XO, ΔMN, and ΔMNO are defined.

[0011]

The second detecting means may employ a configuration in which a spatial frequency of an input image is calculated and a region containing a large number of high frequency components is detected as a main subject region.

[0013]

The input image data is input to the data conversion means, subjected to data conversion processing according to a predetermined data conversion method, and then output to a subsequent circuit. At this time, by the modification means
For the first to fourth representative values MX, MN, MXO and MNO
Change amounts ΔMX, ΔMN, ΔMXO and ΔMNO
Are luminance change data, saturation data, and main subject area
Is defined based on the degree of concentration of
The optimal data conversion method is set variably to the optimal value
Stipulated. This improves the contrast
At the same time, so-called "color blur" is prevented.

[0014]

[0015]

[0016]

[0017]

[0018]

According to the image processing circuit of the present invention, appropriate data conversion is performed in accordance with the characteristics of the input image to be processed, so that the contrast can be improved without lowering the image quality. I can do it.

[0019]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment in which the present invention is applied to a video printer will be described below in detail with reference to the drawings. As shown in FIG. 1, an analog video signal supplied from a video device such as a camera-integrated VTR should be converted into a digital video signal by an A / D converter (1) to form one image. The digital video signal is taken into the image memory circuit (2) as luminance data Y and color difference data U and V.

The data in the image memory circuit (2) is read out by the memory control circuit (4), and further read out by the data conversion circuit.
In (6), it is converted into an RGB signal. At this time, the luminance data Y is input to the look-up table LUT (5), subjected to predetermined data conversion, and output to the data conversion circuit (6). The input / output relationship of the LUT (5) is defined in advance by a circuit described later.

That is, the data in the image memory circuit (2) is supplied to the screen division evaluation circuit (3). Screen division evaluation circuit
(3) shows a case where a plurality of screens (for example, 8 × 8 = 6) are used as shown in FIG.
It is divided into the unit areas of 4), and average luminance data (hereinafter, simply referred to as luminance data) for each unit area is detected.

The luminance data over the entire screen is controlled by the main control circuit.
The maximum value, the minimum value, the average value, and the standard deviation are calculated.

As shown in FIG. 7, the screen has a plurality of screen blocks P ₀ , P ₁ , P ₂ , P ₃ , P ₄ larger than the unit area.
And the average value of the luminance data for each screen block is calculated.

These screen blocks are defined in consideration of the most common screen composition in which one person is located at the center of the screen as shown in FIG. 6, and the screen blocks shown in FIG. P ₂ is the most important region, the screen block P ₀ of the _{surrounding, P 1, P 3, P} 4 is less critical area.

Further, the main control circuit (7) controls the brightness of the entire screen by defining brightness data representing the degree of brightness as shown in FIG.
, Weighting coefficients W ₀ (= 0.1), W ₁ (= 0.2), W ₂ (= 0.3), W ₃ (=
0.2) and W ₄ (= 0.2) are set, and the evaluation luminance value E is calculated by the following equation (1). Where P ₀ , P ₁ , P ₂ ,
P _{3 and} P ₄ represent average values of luminance data for each screen block.

[0026]

E = P ₀ W ₀ + P ₁ W ₁ + P ₂ W ₂ + P ₃ W ₃ + P ₄ W ₄

Then, the average luminance value A for the entire screen
8 and the evaluation luminance value are input to a comparison circuit (9) as shown in FIG. 8, and a magnitude comparison is performed. When A> E, the screen is dark and A = E
When E, the screen brightness is appropriate, and when A <E, it is determined that the screen is bright, and the value of (EA) is defined as brightness data.

The above-described method of defining brightness data has been conventionally employed for determining the brightness of an image by controlling the exposure of a video camera in a camera-integrated VTR.

Further, the saturation of the unit area having the maximum luminance and the saturation of the unit area having the minimum luminance are detected, and these are defined as the saturation data.

The main control circuit (7) performs a frequency analysis on the above-mentioned luminance data to calculate a spatial frequency of the screen, defines a high-frequency region equal to or higher than a predetermined threshold as a main subject region, and sets the main subject region to 1 It is detected whether it exists in a concentrated manner or in a dispersed manner. Further, the maximum luminance and the minimum luminance of the main subject area are calculated. In photographing with a video camera, the autofocus function focuses on the main subject, so that the high-frequency region is the main subject region.

The main control circuit (7) determines the input / output relationship of the LUT (5) based on the screen evaluation data such as the luminance data, standard deviation, brightness data, and saturation data obtained by the above processing. decide.

For example, when the luminance data is represented by 8 bits, the input / output relationship of the LUT (5) is "0" as shown in FIG.
２５ "255" is represented by a one-to-one correspondence between input data and output data. The dashed line in the figure is a case where no data conversion is performed, and as shown by a solid line with respect to the dashed line, the contrast is improved by modifying the high luminance region to have higher luminance and the low luminance region to have lower luminance. I can plan.

In this embodiment, in order to define a polygonal line indicated by a solid line, the maximum luminance point A, the minimum luminance point B, and the main subject area in the entire screen are located between the origin "0" and the maximum point "255". , The maximum luminance point C and the minimum luminance point D are selected. The luminance data at point A is a first representative value MX, the luminance data at point B is a second representative value MN, the luminance data at point C is a third representative value MXO, and the luminance data at point D is a fourth representative value MNO. The positive and negative change amounts ΔMX and ΔMXO for the first representative value MX and the third representative value MXO, respectively, and the negative change amounts ΔMN and ΔMNO for the second representative value MN and the fourth representative value MNO, respectively. To modify the data input / output relationship.

The respective amounts of change are represented by the following equations (2) to (5).

ΔMX = (255−MX) × RA _A

ΔMN = (0−MN) × RA _B

Equation 4] ΔMXO = {(255-MXO) × RA A} × RE C

Equation 5] ΔMNO = {(0-MNO) × RA B} × RE D

Here, RA _A is the rate of change at point _A , RA _B is B
It represents the rate of change of points. RE _C is the reliability of point _C , and RED is the reliability of point _{D, and} is set to a value of 1 or less, respectively. If the determination of the main subject area is accurate, the contrast is improved as the change amounts ΔMXO and ΔMNO of the points C and D are large. However, if the determination is incorrect, the contrast of the main subject area is reduced. There is a risk of lowering. In order to prevent this adverse effect, the above-mentioned reliability is defined.

The amounts of change ΔMX, ΔMXO, ΔMN and ΔMNO are determined by the main control circuit (7) by fuzzy inference. In fuzzy inference, the following rules are defined. Rule 1 If the standard deviation is small, change rates RA _A and _R AB are set small. Rule 2 If the standard deviation is large, change rates RA _A and _R AB are set large.

Rule 3 If the brightness data is small, the rate of change RA _A at point _A is set large and the rate of change RAB at point _B is set small. Rule 4 If the brightness data is large, the rate of change RA _A at point _A is set small and the rate of change RAB at point _B is set large.

Rule 5 If the saturation data of the high luminance portion is large, the rate of change RA _A at point _A is set small. Rule 6 If the saturation data of the low luminance portion is large, the rate of change RAB at point _B is set small.

[0039] In rule 7 if the main subject region exists concentrated in one place, reliability RE _C, setting a large RE _D. Rule 8 If the main subject areas are dispersed, the reliability RE
_C, and set small RE _D.

Rule 9 If the luminance data MX at point A and the luminance data MXO at point C are similar, the reliability REC of point _C is set to be large. Rule 10 If the luminance data MN at the point B and the luminance data MNO at the point D are similar, the reliability RED of the point _D is set to be large.

Rule 1 is based on the contrast of an input image.
It acts to weaken the degree of lowering the brightness near the minimum brightness portion and suppress a sudden change in brightness. Rule 2 acts to enhance the contrast of an image originally having a strong contrast by setting the vicinity of the maximum luminance portion to a higher luminance.

Rule 3 acts to raise the curve of FIG. 2 as a whole when the screen is dark, and Rule 4
Operates to lower the curve of FIG. 2 as a whole when the screen is bright, and sets the screen to an appropriate brightness.

Rule 5 is to reduce the degree of high brightness by data conversion for a bright blue portion such as a blue sky, for example, and to prevent a so-called overexposure of a blue sky in which a bright blue is converted to white. In addition, the rule 6 reduces the degree of luminance reduction in, for example, a dark blue portion and prevents dark blue portions from being converted into black, so-called chromatic black loss.

Rule 7 is that, for example, when a person to be a subject is located in the center of the screen, the high-brightness part of the area is set to a higher brightness, and the low-brightness part of the area is set to a lower brightness. Enhances contrast. On the other hand, rule 8
For example, when the persons are dispersedly located on the entire screen, the degree of the high luminance and the low luminance is weakened.

Rules 9 and 10 are for preventing a sudden change due to the approach between the points A and C and the approach between the points B and D in the curve of FIG.

FIG. 5 shows a part of the antecedent part and the consequent part of point A out of the plurality of rules, and FIG.
5 relates to the standard deviation, FIG. 5B relates to the brightness data, and FIG. 5C relates to the saturation data.

Each data is converted into the domain of "0" to "32" by the scaling process, and then the fitness μ is calculated by the membership function of the antecedent part. or,
Consequent is defined to a constant value C ₀ -C ₅ represented by as shown hexadecimal, so-called simplified fuzzy inference is employed.

Therefore, the change rate C as a result of the fuzzy inference is calculated by the following equation 6 in consideration of other rules.

[0049]

(Equation 6)

The rate of change C obtained by this is 0
When 0H is set to 0% and FFH is set to 100%, it is converted into a percentage display.

The reliability R in the change rate RA _A, and RA _B, C point and D point in the points A and B in FIG. 2 in this manner
E _C, the RE _D is calculated, thereby defined the solid sequential line in FIG. 2, so that the input-output relationship is determined.

In this embodiment, the input / output relationship is discretely represented in the LUT (5) as shown in FIG. 3, and data conversion is performed based on the LUT (5). FIG. 4 shows a series of data setting procedures for the LUT (5).

As shown in FIG. 1, the luminance data Y obtained from the memory control circuit (4) is converted by the LUT (5) and output to the data conversion circuit (6). The obtained RGB signals are supplied to the printing control circuit (8) via the main control circuit (7), and the driving of the video printer is controlled.

According to the above-described image processing circuit, not only the contrast of the image can be improved, but also the evaluation is performed by dividing the image, so that the expressive power of important information included in the image can be improved.

Further, since fuzzy inference is used for evaluating the image and determining the input / output relationship, various properties of the screen can be reflected in the change rate and the reliability, whereby the bright blue changes to white. It is possible to solve the problem of "color blur" such as described above.

The description of the above embodiments is for the purpose of illustrating the present invention, and should not be construed as limiting the invention described in the claims or reducing the scope thereof. Further, the configuration of each part of the present invention is not limited to the above-described embodiment, and it is needless to say that various modifications can be made within the technical scope described in the claims. For example, instead of the above-described fuzzy inference, it is also possible to determine the input / output relation using, for example, a neuro process.

[Brief description of the drawings]

FIG. 1 is a block diagram of an image processing circuit according to the present invention.

FIG. 2 is a graph showing an input / output relationship of image data.

FIG. 3 is a table showing the contents of an LUT.

FIG. 4 is a flowchart showing a series of procedures for determining an input / output relationship.

FIG. 5 is a diagram illustrating a fuzzy rule.

FIG. 6 is a diagram illustrating a number of unit areas constituting a screen.

FIG. 7 is a diagram showing a plurality of screen blocks constituting a screen.

FIG. 8 is a block diagram of a comparison circuit.

[Explanation of symbols]

 (2) Image memory circuit (3) Screen division evaluation circuit (4) Memory control circuit (5) LUT (6) Data conversion circuit (7) Main control circuit

Claims (3)

(57) [Claims] 1. A circuit for improving the contrast of an input image and outputting the same, comprising: luminance data representing the luminance of each unit area constituting the input image; and luminance change data representing the degree of luminance variation over the entire input image. First detection means for detecting saturation data representing the saturation of the high-brightness part and low-brightness part in the input image; second detection means for detecting a main subject area in the input image; A first representative value MX and a second representative value MN which are the maximum and minimum values of the luminance data for the whole, and a third representative value MXO and a fourth representative which are the maximum and minimum values of the luminance data in the main subject area. Third detection means for detecting the value MNO, data conversion means for performing data conversion processing on the input image data and outputting the data in accordance with a predetermined data conversion method representing the relationship between the input image data and the output image data; The first representative value MX and each amount of change for the third representative value MXO? Mx and DerutaMXO, second representative value MN and fourth
For the representative value MNO, the change amounts ΔMN and ΔMNO
Correction means for correcting the input / output relationship of the image data, wherein the correction means includes at least the luminance change.
Data, saturation data and the concentration of the main subject area.
Then, each of the change amounts ΔMX, ΔMN, ΔMXO and Δ
An image processing circuit for defining MNO . 2. The correction means according to claim 1, wherein at least when said brightness change data is small , said first representative value MX and
And the variation amounts ΔMX and ΔMN with respect to the second representative value MN are small.
When the luminance change data is large, the change amount ΔMX
And the first condition for setting large ΔMN and the first representative value when the saturation data of the high-luminance portion is large.
The amount of change ΔMX with respect to MX is set small,
When the saturation data is large, the change with respect to the second representative value MN
The second condition for setting the conversion amount ΔMN small, and the case where the main subject region is concentrated in one place
Corresponds to the third representative value MXO and the fourth representative value MNO.
Large change amounts ΔMXO and ΔMNO
When the regions are dispersed, the change amounts ΔMXO and ΔMXO
In order to satisfy the third condition for setting MNO small ,
The change amounts ΔMX, ΔMXO, ΔMN, and ΔMNO are defined.
The image processing circuit according to claim 1, wherein: 3. The method according to claim 2, wherein the second detecting unit is configured to determine a spatial frequency
Calculate the wave number and detect the high frequency region as the main subject region.
The image processing device according to claim 1, wherein the image processing device outputs the image data.