CN104657941B - A kind of image border self-adapting enhancement method and device - Google Patents

A kind of image border self-adapting enhancement method and device Download PDF

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CN104657941B
CN104657941B CN201310604051.0A CN201310604051A CN104657941B CN 104657941 B CN104657941 B CN 104657941B CN 201310604051 A CN201310604051 A CN 201310604051A CN 104657941 B CN104657941 B CN 104657941B
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detail
pixel point
membership degree
image
index
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CN104657941A (en
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谭世恒
孔文海
邓志权
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Actions Technology Co Ltd
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Juxin (zhuhai) Science & Technology Co Ltd
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Abstract

The invention discloses a kind of image border self-adapting enhancement method and device, to solve to exist in the prior art enhancing effect typically, enhancing edge is simultaneously, also enhance and be not intended to enhanced region and noise, and amount of calculation is larger, take it is longer, the problem of poor real.This method is：According to the corresponding neighborhood territory pixel point of the pixel of each in image, the details index of each pixel is obtained；According to the details index of each pixel and default details index threshold, the basic, normal, high details degree of membership of each pixel is obtained；Noise reduction process is carried out for 1 pixel to all low details degrees of membership, the pixel that all low details degrees of membership are less than with 1 carries out edge enhancing processing, obtains final target image.So, can targetedly it be strengthened according to the details of each pixel in image, while suppressing noise, it is ensured that be not in that amount of calculation is smaller in overshoot phenomenon, and implementation process of the present invention, save the calculating time, real-time is preferable.

Description

Image edge self-adaptive enhancement method and device
Technical Field
The present invention relates to image processing technologies, and in particular, to a method and an apparatus for adaptively enhancing an image edge.
Background
The edge of an image refers to a place where local features (such as brightness, texture, etc.) of the image change. The image edge contains rich information, and has important significance in the image processing fields of image segmentation, feature extraction, identification and the like.
Image edge enhancement is one type of image enhancement process. The method is a technical method for emphasizing the edge with larger difference of brightness values (or color tones) of adjacent pixels (or areas) of an image (namely the boundary line of abrupt change of the color tone of the image or the type of a ground object). The image after the image edge enhancement can more clearly display the boundaries of different ground object types or phenomena or the traces of linear images so as to facilitate the identification of different ground object types and the delineation of the distribution range thereof.
In the prior art, there are many methods for implementing image edge enhancement, such as a related mask technique and an unsharp template method, and the related mask technique is: the original image (image) is copied into a positive film and a negative film, and two films with different properties are accurately overlapped, and when the two films are exposed and printed, the two films are mutually staggered by a small distance, so that an image with slightly staggered 'edged' corresponding image is obtained, most of the positive and negative images are offset, and a bright line (or a dark line) appears at the edge part of the image, so that the display effect of projecting the image boundary line from the background is achieved, and the image is enhanced. The principle of the unsharp template method is as follows: firstly, an original image is subjected to low-pass filtering to generate a passivated blurred image, the original image and the blurred image are subtracted to obtain an image with reserved high-frequency components, the high-frequency image is amplified by a parameter and then is superposed with the original image, and therefore the image with the enhanced edge is generated.
The traditional image edge enhancement technology has a general enhancement effect, requires a user to intervene in the image edge technical process, and often has the defects of enhancing edges and enhancing regions and noise which are not desired to be enhanced, which is a common defect of many edge enhancement methods.
Disclosure of Invention
The embodiment of the invention provides a method and a device for adaptively enhancing an image edge, which are used for solving the problems that the enhancement effect is general, the edge is enhanced, and meanwhile, an area which is not desired to be enhanced and noise are enhanced in the prior art.
The embodiment of the invention provides the following specific technical scheme:
in a first aspect, an image edge adaptive enhancement method includes:
obtaining a detail index of each pixel point according to a neighborhood pixel point corresponding to each pixel point in an image, wherein the detail index is an index for measuring the edge strength of the image;
obtaining the low detail membership degree of each pixel point according to the detail index of each pixel point and a preset detail index threshold;
and carrying out noise reduction processing on the pixel points with the low-detail membership degree of 1 in the image, and carrying out edge enhancement processing on the pixel points with the low-detail membership degree of less than 1 in the image to obtain a final target image.
By dividing the membership degree according to the detail index of each pixel in the image, filtering the pixel point with low detail membership degree of 1 and carrying out edge enhancement processing on other pixel points, the membership degree fuzzy division method enables the transition position of the image to be processed more naturally, can effectively remove noise, enhances the area needing enhancement, enhances the sharpness of the image and ensures that the overshoot phenomenon can not occur.
With reference to the first aspect, in a first possible implementation manner, when the image is a color image, before obtaining a detail index of each pixel point according to a neighborhood pixel point corresponding to each pixel point in the image, the method further includes:
performing color space conversion processing on the color image, and converting the color image into a luminance and chrominance YUV space image;
and after obtaining the final target image, the method further comprises the following steps:
recovering the YUV space image after color space conversion into a color image by using the following formula:
where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
By the method, the color image can be converted into a YUV space image which can be subjected to image edge adaptive enhancement processing, and the processed YUV space image can be restored into the color image.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a second possible implementation manner, obtaining a detail index of any pixel point according to a neighborhood pixel point corresponding to the any pixel point in the image includes:
selecting a (2n +1) × (2n +1) neighborhood taking any pixel point as a center in the image, and performing arithmetic mean calculation on the brightness values of all pixel points in the neighborhood to obtain a neighborhood pixel brightness mean value corresponding to any pixel point, wherein n is a positive integer greater than or equal to 1;
and accumulating the square of the difference between the brightness value of each pixel point in the neighborhood and the brightness average value of the neighborhood pixel corresponding to any pixel point to obtain the detail index of any pixel point.
By the method, the detail index of each pixel point in the image can be accurately calculated.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a third possible implementation manner, while obtaining the low detail membership degree of each pixel, the method further includes:
and obtaining the medium detail membership degree and the high detail membership degree of each pixel point according to the detail index of each pixel point in the image and a preset detail index threshold.
By the method, the medium-detail membership degree and the high-detail membership degree are obtained, and different enhancement processing can be performed according to different pixel point detail membership degrees.
With reference to the third possible implementation manner of the first aspect, in a fourth possible implementation manner, obtaining a low-detail membership degree, a medium-detail membership degree, and a high-detail membership degree of any one pixel point according to a detail index of any one pixel point in the image and a preset detail index threshold includes:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership degree and T of any pixel point2And the difference of the detail index of any pixel point is positively correlated with T2And T1Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1If so, the membership degree of the details of any pixel point is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then, the degree of membership and T of the middle detail of any pixel point4And the difference of the detail index of any pixel point is positively correlated with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index of any pixel pointAnd T3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
By the method, the low-detail membership degree, the medium-detail membership degree and the high-detail membership degree of each pixel point in the image can be accurately obtained.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a fifth possible implementation manner, performing noise reduction processing on any pixel point with a low detail membership degree of 1 in the image includes:
screening out the maximum value Maxf, the minimum value Minf and the intermediate value Medf of the brightness of the neighborhood pixels in the neighborhood (2n +1) × (2n +1) taking any pixel with the low-detail membership degree of 1 as the center,
performing median filtering processing on any pixel point with low detail membership degree of 1, if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and is not equal to Minf, keeping the brightness value of any pixel point with low detail membership degree of 1 unchanged; and if the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Medf.
By the method, the noise reduction treatment is carried out on the pixel points with the low detail membership degree of 1, and the noise can be effectively removed.
With reference to the third possible implementation manner of the first aspect, in a sixth possible implementation manner, performing edge enhancement processing on any pixel point in the image with a low detail membership degree smaller than 1 includes:
according to the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium detail membership degree and the high detail membership degree, the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 are weighted and calculated to obtain the edge enhancement weight coefficient of any pixel point with the low detail membership degree smaller than 1;
convolving the brightness value of any pixel point with low detail membership degree smaller than 1 with a Laplace sharpening template to obtain the edge response value of any pixel point with low detail membership degree smaller than 1;
adding the brightness value of any pixel point with low detail membership degree less than 1 with the result of multiplying the edge enhancement weight coefficient and the edge response value of any pixel point with low detail membership degree less than 1, and performing edge enhancement processing on any pixel point with low detail membership degree less than 1 to obtain any pixel point with low detail membership degree less than 1 after edge enhancement.
By the mode, the pixel points with low detail membership less than 1 can be subjected to edge processing according to the medium detail membership and the high detail membership, so that edge enhancement can be effectively performed, and the sharpness of an image is enhanced.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a seventh possible implementation manner, different edge enhancement weight coefficients preset for the medium-level detail membership and the high-level detail membership should satisfy the following conditions: the edge enhancement weight coefficient preset for the high detail membership is greater than 0, and the edge enhancement weight coefficient preset for the high detail membership is less than the edge enhancement weight coefficient preset for the medium detail membership.
By the method, the targeted edge enhancement processing can be performed on the pixel points by adopting different weight coefficients according to different membership.
In a second aspect, an apparatus for adaptively enhancing image edges includes:
the first calculating unit is used for obtaining a detail index of each pixel point according to a neighborhood pixel point corresponding to each pixel point in the image, wherein the detail index is an index for measuring the edge intensity of the image;
the second calculation unit is used for obtaining the low detail membership degree of each pixel point according to the detail index of each pixel point and a preset detail index threshold;
and the image processing unit is used for carrying out noise reduction processing on the pixel points with the low-detail membership degree of 1 in the image and carrying out edge enhancement processing on the pixel points with the low-detail membership degree of less than 1 in the image to obtain a final target image.
Therefore, the membership degree is divided according to the detail index of each pixel in the image, the pixel point with the low detail membership degree of 1 is filtered, and other pixel points are subjected to edge enhancement processing.
With reference to the second aspect, in a first possible implementation manner, when the image is a color image, the image edge adaptive enhancement apparatus further includes:
the conversion unit is used for performing color space conversion processing on the color image before the first calculation unit obtains the detail index of each pixel point according to the neighborhood pixel point corresponding to each pixel point in the image, and converting the color image into a luminance and chrominance YUV space image;
a restoring unit, configured to restore the YUV space image after color space conversion processing into a color image by using the following formula after the final target image is obtained by the image processing unit:
where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
In this way, the conversion unit can convert the color image into a YUV space image capable of performing image edge adaptive enhancement processing, and the recovery unit can recover the processed YUV space image into the color image. .
With reference to the second aspect or the first possible implementation manner of the second aspect, in a second possible implementation manner, the obtaining, by the first computing unit, the detail index of any pixel point according to a neighboring pixel point corresponding to the any pixel point in the image includes:
the first calculating unit selects a (2n +1) × (2n +1) neighborhood taking any pixel point as a center in the image, and performs arithmetic mean calculation on the brightness values of all pixel points in the neighborhood to obtain a neighborhood pixel brightness mean value corresponding to any pixel point, wherein n is a positive integer greater than or equal to 1;
the first calculating unit accumulates the square of the difference between the brightness value of each pixel point in the neighborhood and the brightness average value of the neighborhood pixel corresponding to any pixel point to obtain the detail index of any pixel point.
Therefore, the first calculating unit can accurately calculate the detail index of each pixel point in the image.
With reference to the second aspect or the first possible implementation manner of the second aspect, in a third possible implementation manner, while the second calculating unit obtains the low detail membership degree of each pixel point, the method further includes:
and the second calculating unit obtains the medium detail membership degree and the high detail membership degree of each pixel point according to the detail index of each pixel point in the image and a preset detail index threshold.
Therefore, the second computing unit can obtain the medium detail membership degree and the high detail membership degree, and can perform different enhancement processing according to different pixel point detail membership degrees.
With reference to the third possible implementation manner of the second aspect, in a fourth possible implementation manner, the obtaining, by the second calculating unit, a low-detail membership degree, a medium-detail membership degree, and a high-detail membership degree of any one pixel point according to the detail index of any one pixel point in the image and a preset detail index threshold includes:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership degree and T of any pixel point2And the difference of the detail index of any pixel point is positively correlated with T2And T1Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1If so, the membership degree of the details of any pixel point is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then, the degree of membership and T of the middle detail of any pixel point4And the difference of the detail index of any pixel point is positively correlated with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index and T of any pixel point3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
Therefore, the second calculating unit can accurately obtain the low-detail membership degree, the medium-detail membership degree and the high-detail membership degree of each pixel point in the image.
With reference to the second aspect or the first possible implementation manner of the second aspect, in a fifth possible implementation manner, the performing, by the image processing unit, noise reduction processing on any pixel point with a low detail membership degree of 1 in the image includes:
the image processing unit screens out the neighborhood of (2n +1) × (2n +1) with the center of any pixel point with the low detail membership degree of 1,a maximum value Maxf, a minimum value Minf and a median value Medf of the luminance of the neighborhood pixels, wherein,
the image processing unit performs median filtering processing on any pixel point with low detail membership degree of 1, and if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and not equal to Minf, the brightness value of any pixel point with low detail membership degree of 1 is unchanged; and if the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Medf.
Therefore, the image processing unit carries out noise reduction processing on the pixel points with the low detail membership degree of 1, and can effectively remove noise.
With reference to the third possible implementation manner of the second aspect, in a sixth possible implementation manner, the performing, by the image processing unit, edge enhancement processing on any pixel point in the image with a low detail membership degree smaller than 1 includes:
the image processing unit weights and calculates the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 according to the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium detail membership degree and the high detail membership degree, so as to obtain the edge enhancement weight coefficient of any pixel point with the low detail membership degree smaller than 1;
the image processing unit convolves the brightness value of any pixel point with the low-detail membership degree smaller than 1 with a Laplace sharpening template to obtain an edge response value of any pixel point with the low-detail membership degree smaller than 1;
the image processing unit adds the result of multiplying the brightness value of any pixel point with the low-detail membership degree less than 1 with the edge enhancement weight coefficient and the edge response value of any pixel point with the low-detail membership degree less than 1, and performs edge enhancement processing on any pixel point with the low-detail membership degree less than 1 to obtain any pixel point with the low-detail membership degree less than 1 after edge enhancement.
Therefore, the image processing unit can carry out edge processing on the pixel points with low detail membership less than 1 according to the medium detail membership and the high detail membership, and can effectively carry out edge enhancement and enhance the sharpness of the image.
With reference to the second aspect or the first possible implementation manner of the second aspect, in a seventh possible implementation manner, different edge enhancement weight coefficients preset for the medium-level detail membership and the high-level detail membership should satisfy the following conditions: the edge enhancement weight coefficient preset for the high detail membership is greater than 0, and the edge enhancement weight coefficient preset for the high detail membership is less than the edge enhancement weight coefficient preset for the medium detail membership.
Therefore, the image processing unit can carry out targeted edge enhancement processing on the pixel points by adopting different weight coefficients according to different membership.
By adopting the technical scheme of the invention, the user does not need to intervene in the edge enhancement process, the membership degree is divided according to the detail index of each pixel in the image, the pixel point with the low detail membership degree of 1 is filtered, and other pixel points are subjected to edge enhancement processing, so that the transition position of the image is more natural by the membership degree fuzzy division method, the pointed enhancement can be carried out according to the details of each pixel point in the image, the noise is inhibited, and the overshoot phenomenon is avoided.
Drawings
Fig. 1 is a flowchart illustrating an embodiment of an image edge adaptive enhancement method according to the present invention;
fig. 2 is a schematic diagram of selecting (2n +1) × (2n +1) neighborhoods according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a detail membership curve according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a preferred Laplace sharpening template according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an image edge adaptive enhancement apparatus according to an embodiment of the present invention.
Detailed Description
By adopting the technical scheme of the invention, the edge enhancement process is not required to be interfered by a user, the pointed enhancement can be carried out according to the details of each pixel point in the image, and the noise is inhibited.
An image edge adaptive enhancement method is provided in an embodiment of the present invention, and a preferred embodiment of the present invention is described in detail below with reference to the accompanying drawings.
Referring to fig. 1, a specific processing flow of the image edge adaptive enhancement method includes:
step 101: and obtaining a detail index of each pixel point in the image according to the neighborhood pixel point corresponding to each pixel point in the image, wherein the detail index is an index for measuring the edge intensity of the image.
The embodiment of the present invention can implement edge enhancement on a gray level image and a color image, because the image edge adaptive enhancement method provided by the embodiment of the present invention is only performed on a luminance (Luma, Y) plane, if an image to be enhanced is a color image, before performing step 101, the color image needs to be subjected to color space conversion processing first, and converted into a luminance-chrominance (LumaChroma, YUV) space image.
Specifically, if the original image is a Red Green Blue (RGB) space image, the RGB format image needs to be converted into a YUV space image, as shown in formula one.
Formula one
Where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, describing the color and saturation of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
In practical application, there are many formulas for converting RGB format image into YUV space image, for example, the formulas may also be adoptedTo perform the conversion, preferably, the embodiment of the present invention selects formula one to perform the color space conversion processing.
Obtaining a detail index of any pixel point in the image according to a neighborhood pixel point corresponding to any pixel point in the image, specifically comprising:
firstly, a (2n +1) × (2n +1) neighborhood centered on any pixel point in the image is selected, wherein n is a positive integer greater than or equal to 1.
For example, referring to fig. 2, C in 201 is the any one pixel point, which is a pixel point in a (2n +1) × (2n +1) neighborhood centered on the any one pixel point in the image, if the any one pixel point appears as a pixel point in an image edge in the process of selecting the (2n +1) × (2n +1) neighborhood centered on the any one pixel point in the image, a neighborhood pixel point is selected from an edge opposite to the edge of the image where the any one pixel point is located, for example, see 202, where n is 1.
And then, performing arithmetic mean calculation on the brightness values of all the pixel points in the neighborhood to obtain the neighborhood pixel brightness mean value corresponding to any one pixel point.
And (3) calculating the arithmetic mean value of the brightness values of all the pixel points in the neighborhood by using a formula II:
formula two
Wherein,expressing the brightness average value of the neighborhood pixels corresponding to any pixel point, x expressing the abscissa of any pixel point, y expressing the ordinate of any pixel point, n expressing a positive integer greater than or equal to 1, and f (i, j) being the brightness value of the pixel point with the coordinate (i, j);
and finally, accumulating the square of the difference between the brightness value of each pixel point in the neighborhood and the average brightness value of the neighborhood pixels corresponding to any pixel point, and obtaining the detail index of any pixel point according to a formula III:
formula three
Wherein D (x, y) represents the detail index of any one of the pixel points.
In the embodiment of the present invention, in order to improve the operation efficiency and avoid division operation in the operation process as much as possible, preferably, the arithmetic mean value of the luminance values of all the pixel points in the neighborhood is calculated by formula four, and the detail index of any pixel point is calculated by formula five:
formula four
Formula five
Step 102: obtaining the low detail membership degree of each pixel point of the image according to the detail index of each pixel point in the image and a preset detail index threshold;
and according to the detail index of each pixel point in the image and a preset detail index threshold, the low detail membership degree of each pixel point of the image is obtained, and meanwhile, the medium detail membership degree and the high detail membership degree of each pixel point of the image can also be obtained.
Specifically, obtaining a low detail membership degree, a medium detail membership degree and a high detail membership degree of any pixel point according to the detail index of any pixel point in the image and a preset detail index threshold, including:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership and T of any pixel point2Positively correlated with the difference of detail index of any pixel point, and T2And T1Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1If so, the membership degree of the details of any pixel point is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then, the degree of membership and T of the middle detail of any pixel point4Positively correlated with the difference of detail index of any pixel point, and T4And T3Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index and T of any pixel point3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
Preferably, in the embodiment of the present invention, the low-detail membership degree, the medium-detail membership degree, and the high-detail membership degree of each pixel point of the image may be calculated by a formula six, a formula seven, and a formula eight:
formula six
Formula seven
Equation eight
Wherein, mu1(D(x,y))、μ2(D (x, y)) and μ3(D (x, y)) is the low, medium and high detail membership degrees of any pixel point, and the detail membership degree function curve is shown in FIG. 3.
Each pixel point in the image has corresponding low detail membership, medium detail membership and high detail membership, and the sum of the low detail membership, the medium detail membership and the high detail membership corresponding to each pixel point in the image is 1.
Step 103: and carrying out noise reduction processing on the pixel points with the low-detail membership degree of 1 in the image, and carrying out edge enhancement processing on the pixel points with the low-detail membership degree of less than 1 in the image to obtain a final target image.
Specifically, the noise reduction processing is performed on any one of the pixel points with the low detail membership degree of 1 in all the pixel points of the image, and the noise reduction processing method includes the following steps:
screening out the maximum value Maxf, the minimum value Minf and the intermediate value Medf of the brightness of the neighborhood pixels in the neighborhood (2n +1) × (2n +1) taking any pixel with the low-detail membership degree of 1 as the center, the middle value Medf is a (2n +1) × (2n +1) neighborhood packet centering on any pixel point with low detail membership degree of 1What you want (2n +1)2And sorting the pixel points according to the brightness values, and selecting the brightness values of the pixel points sorted to be the middle.
Carrying out median filtering processing on any pixel point with low detail membership degree of 1, if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and is not equal to Minf, keeping the brightness value of any pixel point with low detail membership degree of 1 unchanged; if the brightness value of any pixel point with low detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with low detail membership degree of 1 is equal to Medf.
Preferably, the formula nine can be applied to perform median filtering processing on any pixel point with low detail membership degree of 1:
formula nine
Specifically, the edge enhancement processing is performed on any one of the pixel points of the image with the low detail membership degree smaller than 1, and the method includes the following steps:
firstly, according to the medium-detail membership degree and the high-detail membership degree of any pixel point with the low-detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium-detail membership degree and the high-detail membership degree, the medium-detail membership degree and the high-detail membership degree of any pixel point with the low-detail membership degree smaller than 1 are weighted and calculated to obtain the edge enhancement weight coefficient of any pixel point with the low-detail membership degree smaller than 1.
Different edge enhancement weight coefficients preset for the medium and high detail membership degrees are k1And k2Wherein, 0 < k2＜k1Preferably, the formula ten may be applied to calculate the edge enhancement weight coefficient of any pixel point with a low detail membership degree smaller than 1:
k(x,y)＝μ2(D(x,y))*k1+μ3(D(x,y))*k2formula ten
k (x, y) is the edge enhancement weight coefficient of any pixel point with low detail membership degree less than 1.
And then, convolving the brightness value of any pixel point with low detail membership degree smaller than 1 with a Laplace sharpening template to obtain the edge response value of any pixel point with low detail membership degree smaller than 1.
In practical application, the edge response value of any pixel point with low detail membership degree smaller than 1 is calculated, a reverse sharpening template and a Laplace sharpening method are generally adopted, and the method selects the Laplace sharpening method to better realize the image edge self-adaptive enhancement effect.
Preferably, the formula eleven can be applied to obtain the edge response value of any one of the pixel points with the low-detail membership degree smaller than 1:
formula eleven
Wherein f isLaplace(x, y) is the edge response value of any pixel point with low detail membership less than 1, LpAnd sharpening the template for the Laplace.
LpIs (2m +1) × (2m +1), wherein m is a positive integer, as shown in fig. 4, in the embodiment of the present invention, L of 3 × 3 is preferablep。
And finally, adding the brightness value of any pixel point with the low-detail membership degree less than 1 with the result of multiplying the edge enhancement weight coefficient and the edge response value of any pixel point with the low-detail membership degree less than 1, and performing edge enhancement processing on any pixel point with the low-detail membership degree less than 1 to obtain any pixel point with the low-detail membership degree less than 1 after edge enhancement.
According to the formula ten and the formula eleven, the formula twelve is optimized in the embodiment of the invention, and edge enhancement processing is performed on any pixel point with low detail membership degree smaller than 1:
g(x,y)＝f(x,y)+k(x,y)*fLaplace(x, y) formula twelve
And g (x, y) is the pixel point after edge enhancement is carried out on any one pixel point with low detail membership degree smaller than 1.
And performing noise reduction processing on all pixel points with low detail membership degree of 1 in all pixel points of the image, and performing edge enhancement processing on all pixel points with low detail membership degree of less than 1 in all pixel points of the image to obtain a final target image F (x, y), which is shown in a formula thirteen.
Formula thirteen
Obtaining a final target image F (x, y) as an image after image edge adaptive enhancement, and if the original image is a color image, after obtaining F (x, y), converting the image from a YUV space image to a color image, see formula fourteen:
fourteen formula
Based on the foregoing embodiments, referring to fig. 5, an embodiment of the present invention further provides an image edge adaptive enhancing apparatus, including: a first calculation unit 501, a second calculation unit 502 and an image processing unit 503, wherein
The first calculating unit 501 is configured to obtain a detail index of each pixel point in the image according to a neighborhood pixel point corresponding to each pixel point in the image, where the detail index is an index for measuring the edge strength of the image;
the second calculating unit 502 is configured to obtain a low detail membership degree of each pixel point of the image according to the detail index of each pixel point in the image and a preset detail index threshold;
the image processing unit 503 is configured to perform noise reduction processing on the pixel point with the low-detail membership degree of 1 in the image, and perform edge enhancement processing on the pixel point with the low-detail membership degree of less than 1 in the image to obtain a final target image.
When the image is a color image, the image edge adaptive enhancement device further comprises:
the conversion unit 500 is configured to perform color space conversion processing on the color image before the first calculation unit obtains the detail index of each pixel point in the image according to the neighborhood pixel point corresponding to each pixel point in the image, and convert the color image into a luminance and chrominance YUV space image;
a restoring unit 504, configured to restore, after the image processing unit obtains the final target image, the YUV space image after the color space conversion processing to a color image by using the following formula:
where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
The first calculating unit 501 obtains the detail index of any pixel point according to the neighborhood pixel point corresponding to any pixel point in the image, and includes:
the first calculating unit 501 selects (2n +1) × (2n +1) neighborhoods centered at any pixel point in the image, and performs arithmetic mean calculation on the brightness values of all pixel points in the neighborhoods to obtain the brightness mean value of the neighborhood pixels corresponding to any pixel point;
the first calculating unit 501 accumulates the square of the difference between the brightness value of each pixel point in the neighborhood and the average brightness value of the neighborhood pixels corresponding to any one pixel point, and obtains the detail index of any one pixel point.
When the second calculating unit 502 obtains the low detail membership degree of each pixel point in the image, the method further includes:
the second calculating unit 502 obtains the medium-detail membership degree and the high-detail membership degree of each pixel point in the image according to the detail index of each pixel point in the image and a preset detail index threshold.
The second calculating unit 502 obtains the low detail membership degree, the medium detail membership degree and the high detail membership degree of any pixel point according to the detail index of any pixel point in the image and a preset detail index threshold, and includes:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership and T of any pixel point2Positively correlated with the difference of detail index of any pixel point, and T2And T1Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1If so, the membership degree of the details of any pixel point is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then any pixel point is selectedDegree of membership and T of medium detail4Positively correlated with the difference of detail index of any pixel point, and T4And T3Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index and T of any pixel point3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is greater than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
The image processing unit 503 performs noise reduction processing on any one of the low-detail pixel points with a membership degree of 1 in all the pixel points of the image, and includes:
the image processing unit 503 screens out the maximum value Maxf, the minimum value Minf and the median value Medf of the brightness of the neighborhood pixels in the neighborhood of (2n +1) × (2n +1) centered on any of the pixel points with the low-detail membership degree of 1, wherein,
the image processing unit 503 performs median filtering on any pixel point with low detail membership degree of 1, and if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and not equal to Minf, the brightness value of any pixel point with low detail membership degree of 1 is unchanged; if the brightness value of any pixel point with low detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with low detail membership degree of 1 is equal to Medf.
The image processing unit 503 performs edge enhancement processing on any one of the pixels with low detail membership less than 1 in all the pixels of the image, including:
the image processing unit 503 weights and calculates the medium-detail membership degree and the high-detail membership degree of any pixel point with the low-detail membership degree smaller than 1 according to the medium-detail membership degree and the high-detail membership degree of any pixel point with the low-detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium-detail membership degree and the high-detail membership degree, so as to obtain an edge enhancement weight coefficient of any pixel point with the low-detail membership degree smaller than 1;
the image processing unit 503 convolves the brightness value of any pixel point with a low-detail membership degree less than 1 with the Laplace sharpening template to obtain an edge response value of any pixel point with a low-detail membership degree less than 1;
the image processing unit 503 adds the result of multiplying the brightness value of any one of the pixel points with the low-detail membership degree less than 1 by the edge enhancement weight coefficient and the edge response value of any one of the pixel points with the low-detail membership degree less than 1, and performs edge enhancement processing on any one of the pixel points with the low-detail membership degree less than 1 to obtain any one of the pixel points with the low-detail membership degree less than 1 after edge enhancement.
Different preset edge enhancement weight coefficients aiming at the medium detail membership and the high detail membership meet the following conditions: the edge enhancement weight coefficient preset for high detail membership is greater than 0, and the edge enhancement weight coefficient preset for high detail membership is less than different edge enhancement weight coefficients preset for medium detail membership.
In summary, according to the image edge adaptive enhancement method and device provided by the embodiments of the present invention, a user is not required to intervene in an edge enhancement process, the membership is divided according to the detail index of each pixel in an image, the pixel with the low membership of 1 is filtered, and other pixel points are subjected to edge enhancement processing.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to encompass such modifications and variations.

Claims (16)

1. An image edge adaptive enhancement method is characterized by comprising the following steps:
obtaining a detail index of each pixel point according to a neighborhood pixel point corresponding to each pixel point in an image, wherein the detail index is an index for measuring the edge strength of the image;
obtaining the low detail membership degree of each pixel point according to the detail index of each pixel point and a preset detail index threshold;
and carrying out noise reduction processing on the pixel points with the low-detail membership degree of 1 in the image, and carrying out edge enhancement processing on the pixel points with the low-detail membership degree of less than 1 in the image to obtain a final target image.
2. The method as claimed in claim 1, wherein when the image is a color image, before obtaining the detail index of each pixel point according to the neighborhood pixel point corresponding to each pixel point in the image, the method further comprises:
performing color space conversion processing on the color image, and converting the color image into a luminance and chrominance YUV space image;
and after obtaining the final target image, the method further comprises the following steps:
recovering the YUV space image after color space conversion into a color image by using the following formula:
where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
3. The method according to claim 1 or 2, wherein obtaining the detail index of any one pixel point according to a neighborhood pixel point corresponding to the any one pixel point in the image comprises:
selecting a (2n +1) × (2n +1) neighborhood taking any pixel point as a center in the image, and performing arithmetic mean calculation on the brightness values of all pixel points in the neighborhood to obtain a neighborhood pixel brightness mean value corresponding to any pixel point, wherein n is a positive integer greater than or equal to 1;
and accumulating the square of the difference between the brightness value of each pixel point in the neighborhood and the brightness average value of the neighborhood pixel corresponding to any pixel point to obtain the detail index of any pixel point.
4. The method according to claim 1 or 2, wherein, while obtaining the low detail membership of each pixel point, the method further comprises:
and obtaining the medium detail membership degree and the high detail membership degree of each pixel point according to the detail index of each pixel point in the image and a preset detail index threshold.
5. The method of claim 4, wherein obtaining the low detail membership degree, the medium detail membership degree and the high detail membership degree of any one pixel point in the image according to the detail index of any one pixel point in the image and a preset detail index threshold comprises:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership degree and T of any pixel point2And the difference of the detail index of any pixel point is positively correlated with T2And T1Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1If so, the membership degree of the details of any pixel point is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then, the degree of membership and T of the middle detail of any pixel point4And detail index of any one of the pixelsIs in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index and T of any pixel point3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
6. The method of claim 1 or 2, wherein the denoising of any pixel point with a low detail membership of 1 in the image comprises:
screening out the maximum value Maxf, the minimum value Minf and the intermediate value Medf of the brightness of the neighborhood pixels in the neighborhood (2n +1) × (2n +1) taking any pixel with the low-detail membership degree of 1 as the center,
performing median filtering processing on any pixel point with low detail membership degree of 1, if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and is not equal to Minf, keeping the brightness value of any pixel point with low detail membership degree of 1 unchanged; and if the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Medf.
7. The method of claim 4, wherein performing edge enhancement on any pixel point in the image with low detail membership less than 1 comprises:
according to the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium detail membership degree and the high detail membership degree, the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 are weighted and calculated to obtain the edge enhancement weight coefficient of any pixel point with the low detail membership degree smaller than 1;
convolving the brightness value of any pixel point with low detail membership degree smaller than 1 with a Laplace sharpening template to obtain the edge response value of any pixel point with low detail membership degree smaller than 1;
adding the brightness value of any pixel point with low detail membership degree less than 1 with the result of multiplying the edge enhancement weight coefficient and the edge response value of any pixel point with low detail membership degree less than 1, and performing edge enhancement processing on any pixel point with low detail membership degree less than 1 to obtain any pixel point with low detail membership degree less than 1 after edge enhancement.
8. The method of claim 7, wherein different edge enhancement weighting factors preset for medium and high detail membership satisfy the following condition: the edge enhancement weight coefficient preset for the high detail membership is greater than 0, and the edge enhancement weight coefficient preset for the high detail membership is less than the edge enhancement weight coefficient preset for the medium detail membership.
9. An image edge adaptive enhancement apparatus, comprising:
the first calculating unit is used for obtaining a detail index of each pixel point according to a neighborhood pixel point corresponding to each pixel point in the image, wherein the detail index is an index for measuring the edge intensity of the image;
the second calculation unit is used for obtaining the low detail membership degree of each pixel point according to the detail index of each pixel point and a preset detail index threshold;
and the image processing unit is used for carrying out noise reduction processing on the pixel points with the low-detail membership degree of 1 in the image and carrying out edge enhancement processing on the pixel points with the low-detail membership degree of less than 1 in the image to obtain a final target image.
10. The apparatus of claim 9, wherein when the image is a color image, the image edge adaptive enhancement apparatus further comprises:
the conversion unit is used for performing color space conversion processing on the color image before the first calculation unit obtains the detail index of each pixel point according to the neighborhood pixel point corresponding to each pixel point in the image, and converting the color image into a luminance and chrominance YUV space image;
a restoring unit, configured to restore the YUV space image after color space conversion processing into a color image by using the following formula after the final target image is obtained by the image processing unit:
where Y denotes the luminance of a pixel, U and V denote the chromaticity of a pixel, and R, G and B are the values of the luminous intensities of red, green and blue in a pixel.
11. The apparatus according to claim 9 or 10, wherein the obtaining, by the first computing unit, the detail index of any one of the pixel points according to the neighborhood pixel point corresponding to the any one of the pixel points in the image comprises:
the first calculating unit selects a (2n +1) × (2n +1) neighborhood taking any pixel point as a center in the image, and performs arithmetic mean calculation on the brightness values of all pixel points in the neighborhood to obtain a neighborhood pixel brightness mean value corresponding to any pixel point, wherein n is a positive integer greater than or equal to 1;
the first calculating unit accumulates the square of the difference between the brightness value of each pixel point in the neighborhood and the brightness average value of the neighborhood pixel corresponding to any pixel point to obtain the detail index of any pixel point.
12. The apparatus according to claim 9 or 10, wherein, while the second calculation unit obtains the low detail membership degree of each pixel point, it further comprises:
and the second calculating unit obtains the medium detail membership degree and the high detail membership degree of each pixel point according to the detail index of each pixel point in the image and a preset detail index threshold.
13. The apparatus of claim 12, wherein the second calculating unit obtains a low detail membership degree, a medium detail membership degree and a high detail membership degree of any one of the pixel points according to the detail index of any one of the pixel points in the image and a preset detail index threshold, and comprises:
if the detail index of any pixel point is less than or equal to T1If so, the low detail membership degree of any pixel point is 1; if the detail index of any pixel point is more than T1And is less than T2Then, the low detail membership degree and T of any pixel point2And the difference of the detail index of any pixel point is positively correlated with T2And T1Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T2If so, the low detail membership degree of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T1Then, the middle detail of any pixel pointThe degree of membership is 0; if the detail index of any pixel point is more than T1And is less than T2Then, the degree of membership of the middle details of any pixel point and the detail index and T of any pixel point1Is in positive correlation with T2And T1Negative correlation of the difference; if the detail index of the pixel point is more than or equal to T2And is less than or equal to T3If so, the membership degree of the details of any pixel point is 1; if the detail index of any pixel point is more than T3And is less than T4Then, the degree of membership and T of the middle detail of any pixel point4And the difference of the detail index of any pixel point is positively correlated with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the membership degree of the details of any pixel point is 0;
if the detail index of any pixel point is less than or equal to T3If so, the high detail membership degree of any pixel point is 0; if the detail index of any pixel point is more than T3And is less than T4Then, the high detail membership degree of any pixel point and the detail index and T of any pixel point3Is in positive correlation with T4And T3Negative correlation of the difference; if the detail index of any pixel point is more than or equal to T4If so, the high detail membership degree of any pixel point is 1;
wherein, T1、T2、T3And T4Is a preset detail index threshold value and satisfies 0 < T1＜T2＜T3＜T4。
14. The apparatus according to claim 9 or 10, wherein the image processing unit performs noise reduction processing on any pixel point with low detail membership degree of 1 in the image, and comprises:
the image processing unit screens out the maximum value of the brightness of the neighborhood pixels in a (2n +1) × (2n +1) neighborhood taking any pixel point with the low-detail membership degree of 1 as the centerMaxf, a minimum value Minf, and a median value Medf, wherein,
the image processing unit performs median filtering processing on any pixel point with low detail membership degree of 1, and if the brightness value of any pixel point with low detail membership degree of 1 is not equal to Maxf and not equal to Minf, the brightness value of any pixel point with low detail membership degree of 1 is unchanged; and if the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Maxf or Minf, the brightness value of any pixel point with the low-detail membership degree of 1 is equal to Medf.
15. The apparatus of claim 12, wherein the image processing unit performs edge enhancement on any pixel point in the image with low detail membership less than 1, and comprises:
the image processing unit weights and calculates the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 according to the medium detail membership degree and the high detail membership degree of any pixel point with the low detail membership degree smaller than 1 and different preset edge enhancement weight coefficients aiming at the medium detail membership degree and the high detail membership degree, so as to obtain the edge enhancement weight coefficient of any pixel point with the low detail membership degree smaller than 1;
the image processing unit convolves the brightness value of any pixel point with the low-detail membership degree smaller than 1 with a Laplace sharpening template to obtain an edge response value of any pixel point with the low-detail membership degree smaller than 1;
the image processing unit adds the result of multiplying the brightness value of any pixel point with the low-detail membership degree less than 1 with the edge enhancement weight coefficient and the edge response value of any pixel point with the low-detail membership degree less than 1, and performs edge enhancement processing on any pixel point with the low-detail membership degree less than 1 to obtain any pixel point with the low-detail membership degree less than 1 after edge enhancement.
16. The apparatus of claim 15, wherein different edge enhancement weighting factors preset for medium and high detail membership satisfy the following condition: the edge enhancement weight coefficient preset for the high detail membership is greater than 0, and the edge enhancement weight coefficient preset for the high detail membership is less than the edge enhancement weight coefficient preset for the medium detail membership.
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