JPH06339017A - Saturation emphasizing method and device for color picture - Google Patents

Abstract

PURPOSE:To emphasize the saturation of a picture by obtaining the maximum value of the R, G, and B values of each picture element as I, multiplying a difference between the I and each R, G, and B value by an emphasis coefficient, and obtaining a value obtained by subtracting the result from the I as the new R, G, and B values. CONSTITUTION:The maximum value I of the R, G, and B data of an input picture memory 1 is calculated for each picture element by a maximum value calculating means 2. Also, an emphasis coefficient (a) is preliminarily inputted from a coefficient inputting means 5. Then, the arithmetic operation of multiplying the difference between the maximum I and each RGB value by the emphasis coefficient (a) for each element of the memory 1, and subtracting the result from the I is performed by an RGB picture element arithmetic means 3. Then, the output of the arithmetic means 3 is stored as the new R, G, and B values in an output picture memory 4. When the emphasis coefficient is more than 1, the saturation is emphasized, when it is less than 1, the saturation is decreased, and when it is 0, complete no-saturation is obtained. Therefore, the adjustment of the saturation in a wide range from the no-saturation to the bright color can be attained.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a technique for adjusting the color saturation of an image in a television, a scanner, a facsimile or the like.

[0002]

2. Description of the Related Art Conventionally, in order to emphasize the saturation of a color image, RGB data is decomposed into three components of lightness, saturation and hue, and only the saturation component is looked up in a lookup table (LU).
T) is used for conversion, and then RGB reverse conversion is performed.

As an example, as shown in FIG. 5, the RGB data in the input image memory 41 is converted into, for example, L ^* C ^* H ^* coordinates by the color coordinate conversion means 42, and the saturation C ^* is converted into the saturation conversion means 46. Then, the color coordinate reverse conversion means 47 performs reverse conversion into RGB. As an example of the saturation conversion means 46, there is a method of converting the saturation by referring to a lookup table having characteristics such as the saturation conversion function 49 of FIG. RGB to L
The conversion formula to ^* C ^* H ^* is described in detail in the document JIS-Z8729.

[0004]

A conventional color image saturation enhancement apparatus requires conversion processing for decomposing RGB signals into lightness, saturation, and hue components, which requires a large amount of calculation time and memory. There was a drawback.

Further, in order to improve the image quality of the output image, the LUT for converting the saturation component must be optimally determined, but conventionally there is a drawback that this must be manually adjusted.

SUMMARY OF THE INVENTION It is an object of the present invention to solve the above drawbacks and to provide a chroma enhancement device which is very fast and requires less memory. Another object of the present invention is to provide a saturation emphasizing device capable of automatically performing saturation emphasis for high image quality.

[0007]

According to a first aspect of the present invention, there is provided a color image saturation enhancement method, wherein I is a maximum value of R, G and B values of each pixel of the color image, and I and each R, G and B value. The difference from the value is multiplied by the emphasis coefficient, and the result is subtracted from I to obtain a new R,
It is characterized in that the saturation of the image is emphasized by setting the G and B values.

A color image saturation enhancement method according to a second aspect of the present invention is the same as the first aspect of the present invention, wherein R,
The maximum value of the G and B values is I, the minimum value is i, and the difference between I and i is divided by I to calculate the saturation for each pixel, and the maximum saturation value in the image or the saturation value in the image is calculated. The maximum saturation value is obtained in a high lightness region, and the enhancement coefficient is determined as a function of the maximum saturation value.

According to a third aspect of the present invention, there is provided a color image saturation enhancement method according to the first aspect, wherein R,
The maximum value of the G and B values is I, the minimum value is i, the difference between I and i is divided by I, and the saturation is calculated for each pixel. It is characterized in that the maximum saturation value in the filtered image or the maximum saturation value in a high lightness region in the image is obtained, and the enhancement coefficient is determined as a function of the maximum saturation value.

A color image saturation enhancing apparatus according to a fourth aspect of the present invention provides an R, R,
Maximum value calculation means for calculating the maximum value I of G and B, coefficient input means for inputting the emphasis coefficient a, I and R for each pixel
RG that multiplies the difference from the GB value by the emphasis coefficient a and subtracts the result from I to obtain new R, G, B values
It is characterized by comprising B pixel calculating means.

According to a fifth aspect of the present invention, in the color image saturation emphasizing apparatus according to the fourth aspect, the maximum value I of R, G, B of each pixel is input from the input color image memory instead of the coefficient input means.
And a minimum value i, and a saturation calculation unit that calculates the saturation by performing a calculation of dividing the difference between the maximum value I and the minimum value i by the maximum value I, and a color that stores the output of the saturation calculation unit. Saturation image memory, maximum saturation value extraction means for extracting the maximum saturation value as the maximum value in the saturation image memory, and emphasis coefficient calculation means for calculating the emphasis coefficient a as a function of the maximum saturation value. It is characterized by

According to a sixth aspect of the present invention, in the color image saturation enhancing apparatus according to the fourth aspect of the present invention, the maximum value I and the minimum value of R, G, B of each pixel 4 from the input color image memory are used instead of the coefficient input means. A saturation calculation unit that calculates a value i and performs a calculation of dividing a difference between the maximum value I and the minimum value i by the maximum value I, and a saturation image that stores an output of the saturation calculation unit. The brightness is constant by referring to the memory, the brightness calculation unit that calculates the brightness of each pixel from the input color image memory, the brightness image memory that stores the output of the brightness calculation unit, and the values of the brightness image memory and the saturation image memory. As a maximum value of the saturation in the pixels in the range, a maximum saturation value extracting means for extracting the maximum saturation value and an emphasis coefficient calculating means for calculating an emphasis coefficient a as a function of the maximum saturation value are provided. Characterize.

The color image saturation emphasizing apparatus according to the seventh aspect of the present invention is the color image saturation enhancing apparatus according to the fifth or sixth aspect, further comprising a filtering operation unit that performs a low-pass filtering operation on the saturation image data after the saturation image memory. Is characterized by.

In the saturation enhancing apparatus for color image of the eighth invention, the enhancement coefficient calculating means in the fifth, sixth or seventh invention has a = 1 / S as a function of the maximum saturation S _max.
The feature is that the emphasis coefficient a is calculated by calculating _max .

[0015]

The principle of the color image saturation enhancement method according to the first aspect of the present invention will be described below.

FIG. 7 is a diagram for explaining the principle of the saturation enhancement method of the present invention, showing changes in R, G and B values before and after the saturation enhancement. When the maximum value 51 of RGB before emphasis is I, the intermediate value 52m of RGB before emphasis is i, and the minimum value 53 of RGB before emphasis is i, the white component of this pixel before emphasis is represented by W in FIG. It becomes the white component 55. The white component 55 is R, G,
Each of B contains the same value as i. Therefore, the color component 58 of this pixel is the remaining component obtained by subtracting the white component 55 from RGB.

The saturation enhancement method of the present invention performs a process of decreasing the ratio of the white component 55 in order to increase the ratio of the color component in the pixel value.

In this processing, the maximum value 51 is considered to represent the brightness of the pixel, and the maximum value 51 does not change before and after the enhancement. Further, since the hue is preserved before and after the emphasis, the ratio of the two components in the color component 58 does not change. That is, the ratio of the difference 56 between the maximum value and the intermediate value and the difference 57 between the intermediate value and the minimum value is constant before and after the emphasis.

Therefore, the saturation enhancement method of the present invention uses the enhancement coefficient 59 (symbol is a) as the enhancement parameter. Maximum value 61 (I ') after emphasis and minimum value 63 after emphasis
(I ') and the intermediate value 62 (m') after emphasis are obtained by the calculation of the following equation.

I ′ = I, m ′ = I− (I−m) a, i ′ = i− (I−i) a (1) From the above, when the enhancement coefficient 59 is greater than 1.0, the post-emphasis is performed. The white component 65 is less than the white component 55 before the enhancement, and the saturation is enhanced. When the emphasis coefficient 59 is smaller than 1.0, the white component 65 after emphasis is the white component 55 before emphasis.
And the saturation is reduced. When the enhancement coefficient 59 is 1.0, there is no color change before and after the enhancement. Emphasis factor 5
When 9 is 0.0, the emphasized pixel is achromatic. Further, it can be seen that the ratio of the difference 66 between the maximum value and the intermediate value and the difference 67 between the intermediate value and the minimum value after the enhancement is the same as that before the enhancement, and the hue is preserved.

The principle of the color image saturation enhancement method of the second invention will be described below.

The present invention is the addition of a method for determining an emphasis coefficient in the color image saturation emphasis method of the first invention.

When the maximum value of the R, G, B values of each pixel of the input color image is I and the minimum value is i, the value obtained by dividing the difference between I and i by I is the saturation S of that pixel. .

S = (I−i) / I (2) This saturation value indicates the ratio of the part excluding the white component 55 in the maximum value 51 in FIG. Is a valid definition of. This saturation is 0.0 to 1.0
It is defined in the range up to.

Next, the saturation is calculated for each pixel, and the maximum value S _max of the saturation in the image is obtained. Then, the enhancement coefficient 59 is obtained as a function of the maximum value S _max of the saturation.

FIG. 8 shows an example of a function for obtaining the emphasis coefficient. S _{max on the} horizontal axis is the maximum value of saturation, and the vertical axis is the emphasis coefficient. Examples of the function include a first function 71 and a second function 72. In an actual device, a function may be stored as a look-up table and referred to as needed.

When the saturation S of the input image is plotted on the horizontal axis and the saturation S'of the output image is plotted on the vertical axis as shown in FIG. 9, the emphasis coefficient 59 in FIG. It represents the slope of a straight line passing through the origin. Therefore, if a pixel whose saturation of the input image is S _max is set to 1.0 in the output, the inclination is 1 / S as in the saturation conversion function 81 of FIG.
_{Since it is} a straight line of _max , the emphasis coefficient a can be expressed by the following equation.

A = 1 / S _max (3) When this is expressed in the graph of FIG. 8, it has a form like the second function 72.

Further, there is a method of obtaining the maximum value of the saturation in the high lightness portion of the image, instead of obtaining the maximum value of the saturation of the entire screen of the input image to obtain the maximum value S _max of the saturation. . Using the saturation definition from equation (2),
In low lightness, no matter how large the saturation is, the color does not become vivid. Therefore, only where the brightness is high,
By _obtaining S _max as a target, the enhancement coefficient a adapted to human color perception can be determined.

When the emphasis coefficient is determined as described above, the saturation is emphasized by the saturation emphasis method of the first invention based on this value.

The principle of the image saturation enhancement method of the third invention will be described below. The present invention is a modification of the method for determining the enhancement coefficient in the image saturation enhancement method of the second invention.

In the present invention, after the saturation is calculated for each input image, the low-pass filtering action is performed. From the output low-frequency saturation image, the maximum saturation S _max is obtained. The following processing is the same as the saturation enhancement method of the second invention.

According to the knowledge about human sense, it is known that the influence of the low frequency component is much larger than that of the high frequency component on the saturation of the image. Therefore, even if the low frequency is filtered, there is almost no effect on the saturation, and conversely, when the input image contains a noise component, it is possible to remove the effect.

[0034]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An image saturation enhancing apparatus according to an embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows an embodiment of an image saturation enhancing apparatus according to the fourth invention. From the R, G, and B data of the input image memory 1, the maximum value calculation means 2 calculates each pixel,
The maximum value I of R, G and B is calculated.

Further, the emphasis coefficient a is input from the coefficient input means 5 in advance.

Then, in the RGB pixel calculation means 3, the difference between the maximum value I and each RGB value is multiplied by the emphasis coefficient a for each pixel of the input image memory 1, and the result is subtracted from I. Then, the output of the RGB pixel calculation means 3 is stored in the output image memory 4 as new R, G, B values.

FIG. 2 shows an embodiment of the image saturation enhancing apparatus of the fifth invention. The image saturation enhancing apparatus according to the fourth aspect of the invention has the following coefficient calculating means 14 instead of the coefficient inputting means 5.

The coefficient calculating means 14 calculates the saturation from the input image memory 1 by the saturation calculating means 11 and stores the output in the saturation image memory 12. Saturation calculation means 11
Calculates the maximum value I and the minimum value i of RGB for each pixel of the input image memory 1 and calculates the saturation by calculating (I−i) / I. Next, the maximum saturation value extraction unit 13 sets the maximum saturation value S as the maximum value in the saturation image memory 12.
Extract _max .

The emphasis coefficient a is obtained by the saturation maximum value changing means 15 as a function of the saturation maximum value S _max . As an example of the saturation maximum value conversion means 15, a device for converting a function such as the first function 71 or the second function 72 of FIG. 8 by a programmed mathematical formula, or data stored in advance. , A device referred to as a lookup table, and the like.

Based on the obtained enhancement coefficient a, each pixel is calculated by the same method as in the image saturation enhancing apparatus of the fourth invention to enhance the saturation.

FIG. 3 shows an embodiment of an image saturation enhancing apparatus of the sixth invention. The image saturation enhancing apparatus according to the fourth aspect of the invention has the following coefficient calculating means 24 instead of the coefficient inputting means 5.

The coefficient calculating means 24 calculates the saturation from the input image memory 1 by the saturation calculating means 11 and stores the output in the saturation image memory 12. At the same time, the RGB value of each pixel is read from the input image memory 1 by the brightness calculating means 21.
The maximum value I of is stored in the brightness image memory 22. Considering that the maximum value I is representative of the brightness of the pixel has been described in the section of action.

The saturation calculating means 11 is the input image memory 1
The maximum value I and the minimum value i of RGB are calculated for each pixel of
(I-i) / I is calculated to calculate the saturation.

Next, the maximum saturation value extraction means 23 refers to the brightness image memory 22 to obtain the maximum saturation value S _max as the maximum saturation value in the high brightness area.
The reason for considering the brightness is described in the section of action.

The emphasis coefficient a is obtained by the saturation maximum value conversion means 15 as a function of the saturation maximum value S _max . An example of the saturation maximum value conversion means 15 has been described in the section of the saturation emphasis device of the fifth invention.

Based on the obtained enhancement coefficient 6, each pixel is calculated by the same method as the image saturation enhancing apparatus of the fourth aspect of the invention to enhance the saturation.

FIG. 4 shows an embodiment of the image saturation emphasizing apparatus of the seventh invention. FIG. 4 replaces the coefficient calculating means 14 of FIG. According to the present invention, in the image saturation emphasizing device of the fifth and sixth inventions, the low-pass filtering means 31 applies a low-pass filtering action to the data in the saturation image memory 12.

Thereafter, the enhancement coefficient a is obtained in the same manner as in the image saturation enhancing device of the fifth and sixth inventions. Then, based on the obtained enhancement coefficient a, each pixel is calculated by the same method as the image saturation enhancing apparatus of the fourth aspect of the invention to enhance the saturation.

For application to the saturation emphasizing device of the sixth invention, the low-pass filtering means 31 is provided between the saturation image memory 12 and the maximum saturation value extracting means 23 of FIG.

FIGS. 2, 3 and 4 show an embodiment of the image saturation enhancing apparatus of the eighth invention. In the fifth, sixth, and seventh image saturation enhancement devices, as the enhancement coefficient calculation means 15, a means for operating the following function is implemented.

A = 1 / S _max (4) Examples of the emphasis coefficient calculation means 15 include programmed mathematical expressions and means for pre-storing data and referencing it as a lookup table.

As a result, when S _max is large, the saturation of the input image is high, so that the emphasis coefficient a becomes low, and when S _max is small, the emphasis coefficient a becomes large. S
When max is 0, an appropriate value is set as a.

[0054]

EFFECTS OF THE INVENTION It is possible to enhance the saturation of a color image of RGB values without converting it to another coordinate system and changing the hue. Moreover, the processing time is short. The emphasis coefficient is 1.0
When it is larger than 1.0, the saturation is emphasized, but when it is smaller than 1.0, the saturation can be decreased, and at 0.0, the color is completely achromatic. When 1.0, the original image does not change at all. Therefore, saturation can be adjusted in a wide range from achromatic colors to vivid colors.

Further, the saturation enhancing apparatus of the fifth, sixth and seventh inventions can automatically enhance the saturation of an image so that the image quality is visually high.

Further, the saturation emphasizing device of the eighth aspect of the present invention is capable of correcting human eyes subjectivity when calculating the correction coefficient without being influenced by the noise component of the original image.

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of a color image saturation enhancement device of a third invention.

FIG. 2 is a block diagram showing an embodiment of a color image saturation enhancing device of a fourth invention.

FIG. 3 is a block diagram showing an embodiment of a color image saturation enhancement apparatus of a fifth invention.

FIG. 4 is a block diagram showing an embodiment of a color image saturation enhancement device of a sixth invention.

FIG. 5 is a block diagram showing an embodiment of a conventional color image saturation enhancement device.

6 is an example of a saturation conversion function used in the saturation conversion means 46 of FIG.

FIG. 7 is a diagram for explaining an image saturation enhancement method of the first invention.

FIG. 8 is an example of an enhancement coefficient calculation function.

[Fig. 9] Relationship between saturation of input image and saturation of output image

[Explanation of symbols]

 1, 41 Input image memory 2 Maximum value calculation device 3 RGB pixel calculation means 4, 48 Output image memory 5 Coefficient input means 11 Saturation calculation means 12 Saturation image memory 13, 23 Maximum saturation value extraction means 14, 24 Coefficient calculation Means 15 Maximum chroma conversion means 21 Brightness calculation means 22 Brightness image memory 23 Enhancement coefficient calculation means 31 Low-pass filtering means 42 Color coordinate conversion means 43 L image memory 44 C image memory 45 H image memory 46 Saturation conversion means 47 colors Coordinate inverse conversion means 49, 81 Saturation conversion function 51 Maximum value I 52 Intermediate value m 53 Minimum value i 54 Difference between maximum value and minimum value 55 White component 56 Difference between maximum value and intermediate value 57 Difference between intermediate value and minimum value 58 color components 59 enhancement coefficient 61 maximum value after conversion I 62 intermediate value after conversion m 63 minimum value after conversion i 64 difference between maximum value and minimum value after conversion 5 white component 66 post-conversion maximum value and intermediate value and the color component 71 first function 72 a second function after a difference 68 converts the minimum value after the difference 67 converts the intermediate value of the converted

Claims (8)

[Claims] 1. A method in which the maximum value of R, G, B values of each pixel of a color image is I, the difference between I and each R, G, B value is multiplied by an emphasis coefficient, and the result is subtracted from I. The new R, G,
A saturation enhancement method for a color image, wherein the saturation of the image is enhanced by setting the B value. 2. Saturation is calculated for each pixel, where I is the maximum value of R, G, B values of each pixel of the color image, i is the minimum value, and the difference between I and i is divided by I. Then, the maximum saturation value in the image or the maximum saturation value in a high lightness region in the image is obtained, and the enhancement coefficient is determined as a function of the maximum saturation value. Saturation enhancement method for color images. 3. A saturation which is a value obtained by dividing a difference between I and i by I is calculated for each pixel, where I is a maximum value of R, G and B values of each pixel of a color image and i is a minimum value. Then, the saturation maximum value in the image obtained by subjecting the image data of the obtained saturation to the low-pass filtering or the saturation maximum value in the area with high lightness in the image is obtained, and as a function of the maximum saturation value, The color image saturation enhancement method according to claim 1, wherein the enhancement coefficient is determined. 4. A maximum value calculating means for calculating a maximum value I of R, G, B for each pixel from an input color image memory, a coefficient input means for inputting an emphasis coefficient a, and I for each pixel. And an RGB pixel calculating means for multiplying the difference between each RGB value by an emphasis coefficient a and subtracting the result from I to obtain new R, G, B values. Saturation enhancement device. 5. The maximum value I and the minimum value i of R, G, B of each pixel are calculated from the input color image memory instead of the coefficient input means, and the difference between the maximum value I and the minimum value i is calculated as the maximum value. Saturation calculating means for calculating the saturation by performing an operation of dividing by I, a saturation image memory for storing the output of the saturation calculating means, and a maximum saturation as the maximum value in the saturation image memory. 5. The color image saturation enhancement apparatus according to claim 4, further comprising: a maximum saturation value extraction means for extracting a value; and an enhancement coefficient calculation means for calculating an enhancement coefficient a as a function of the maximum saturation value. 6. The maximum value I and the minimum value i of R, G, B of each pixel are calculated from the input color image memory instead of the coefficient input means, and the difference between the maximum value I and the minimum value i is calculated as the maximum value. Saturation calculating means for calculating saturation by performing an operation of dividing by I, saturation image memory for storing the output of the saturation calculating means, and brightness for calculating the brightness of each pixel from the input color image memory Calculating means, a brightness image memory for storing the output of the brightness calculating means, with reference to the values of the brightness image memory and the saturation image memory, as the maximum value of the saturation in pixels in which the brightness is in a certain range, The saturation of a color image according to claim 4, further comprising: a maximum saturation value extracting means for extracting the maximum saturation value; and an emphasis coefficient calculating means for calculating an emphasis coefficient a as a function of the maximum saturation value. Emphasis device. 7. A color image saturation enhancing apparatus according to claim 5, further comprising low-pass filtering means for applying low-pass filtering to the saturation image data, which is provided downstream of said saturation image memory. . 8. The saturation coefficient calculation means is configured to set a maximum saturation value S.
_8. The color image saturation enhancement device according to claim 5, wherein the enhancement coefficient a is calculated as a function of _max by calculating a = 1 / S _max .