CN113129389B - Method for judging moire, method for inhibiting moire and circuit system - Google Patents
Method for judging moire, method for inhibiting moire and circuit system Download PDFInfo
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Abstract
In the method, brightness values of a plurality of pixels in an image are obtained, a plurality of key pixels for judging the moire type can be selected from a detection window, a moire response value of the plurality of key pixels and a plurality of adjacent pixels corresponding to the key pixels respectively is calculated for each pixel through the detection window, brightness values of the key pixels and the adjacent pixels are compared through the detection window, the comparison result is counted to judge brightness characteristics of each pixel, and then the moire position and the moire type in the image can be confirmed according to the moire response value and the counted result. Then, color noise reduction is performed on the plurality of pixels determined to be moire.
Description
Technical Field
The present invention relates to a technology for determining moire, and more particularly, to a method for determining moire by detecting moire in different directions and counting a characteristic comparison value of the moire, a method for suppressing the determined moire, and a circuit system for implementing the method.
Background
Among the imaging defects commonly found in digital images, moire is a common cause of moire formation because a photosensitive element (such as a CCD or CMOS) in an image sensor is subjected to high frequency interference when image data is acquired, such as taking a photograph with a digital camera, taking a film with a digital video camera or taking an image with a scanner, and color and shape irregularities, called moire, appear on the image.
In addition, when an object with dense lines (such as textile, lines with high repeatability, a display screen, etc.) is photographed, if the pixel sampling frequency of the photosensitive component is close to the spatial frequency of the lines on the object, a low-frequency line can be generated on the image, meanwhile, due to the use of a Bayer Filter, the sampling rate of red, green and blue visible light is different, color noise is often accompanied on the mole lines, and the result actually seen by human eyes is not met.
In order to solve the moire phenomenon, when manufacturing a camera or adding an optical Low-pass filter (Low-PASS FILTER) on a lens, although helping to reduce the moire phenomenon, partial image details are lost. In addition, the post-processing is performed in the image signal Processor (IMAGE SIGNAL Processor, ISP), so that the position where the brightness change of the pixel is low and the color change is high can be judged as the position where the moire occurs, and the color compensation can be performed according to the adjacent pixels, but therefore, the saturation (saturation) may be reduced.
Thus, the method disclosed in the prior art cannot accurately detect the moire, if there is a false judgment, the color quality of the image is reduced, and the mechanism of color compensation may be limited by hardware limitation, so that the moire cannot be completely eliminated.
Disclosure of Invention
The invention discloses a method for judging moire, a method for inhibiting moire and a circuit system for realizing the method, wherein one of the purposes is to process moire (moire Pattern) in a digital image by utilizing an image processing technology, comprising detecting the position of the moire, and one of the purposes is to reduce color noise at the position where the moire occurs, so that an imaging result is more in line with human eyes' visual perception.
According to an embodiment of the method for determining moire, luminance information of a plurality of pixels in an image, such as a luminance value in a YUV (luminance-chrominance-concentration) color space or an average value of three color channel values in an RGB (red-green-blue) color space, is obtained first, then a detection window is provided, a plurality of key pixels for determining moire type are selected in the detection window, and then a moire response value of the plurality of key pixels in the detection window and a plurality of adjacent pixels corresponding to each key pixel is calculated for each pixel one by one, which can be used to determine whether the image has moire features.
And then, comparing brightness values of a plurality of key pixels and a plurality of corresponding adjacent pixels by utilizing a detection window for each pixel, and counting comparison results to judge brightness characteristics of each pixel, so that the positions and types of the moire in the image can be confirmed according to the moire response values and the counting results.
Preferably, in the step of calculating the moire response value, a weight mask is set in the detection window, and the weight mask may be designed according to the moire type to be determined, including assigning a higher weight value to a plurality of key pixels, assigning a lower weight value to a plurality of neighboring pixels, and multiplying the weight values by the plurality of key pixels and the corresponding plurality of neighboring pixels, respectively, to calculate the moire response value.
Further, the calculated moire response value of each pixel can be compared with the first threshold value to obtain brightness variation of the pixel and the adjacent pixels, and whether the image has moire features or not can be further judged. In addition, when comparing the brightness information of the plurality of key pixels and the plurality of adjacent pixels corresponding to each other, a second threshold may be introduced to confirm the brightness characteristics of each pixel.
The types of the mole patterns are mole patterns in the horizontal and vertical directions, mole patterns in the main diagonal directions or mole patterns in the secondary diagonal directions.
Further, color moire suppression may be performed for the relevant pixel determined as moire, including that a plurality of pixels determined as moire may be mapped to a chromaticity-density plane of a luminance-chromaticity-density color space, and then pixel colors within a color suppression range in the chromaticity-density plane may be suppressed to gray scale, and further, the chromaticity-density plane may further distinguish a color suppression progressive range, and a suppression magnification may be set for a distance between a pixel color within the color suppression progressive range and a coordinate center of the chromaticity-density plane, within the color suppression progressive range, color suppression may be performed according to the suppression magnification.
According to the embodiment of the circuit system, a digital image processor may be provided, wherein the method for determining moire and the method for suppressing moire are performed.
For a further understanding of the nature and the technical aspects of the present invention, reference should be made to the following detailed description of the invention and to the accompanying drawings, which are provided for purposes of illustration only and are not intended to limit the invention.
Drawings
FIG. 1 is a functional block diagram illustrating an embodiment of circuitry implementing a method for determining and suppressing moire;
FIG. 2 is a flow chart illustrating an embodiment of a method of determining and suppressing moire;
Fig. 3 is a schematic view showing an example of judging the moire direction in the method of judging moire;
FIGS. 4A and 4B are schematic diagrams showing horizontal and vertical moire, respectively;
fig. 5A to 5C are schematic views showing a method of judging moire in horizontal and vertical directions;
fig. 6A to 6C are schematic views showing a method of judging a main diagonal direction moire;
Fig. 7A to 7C are schematic views showing a method of judging the minor diagonal direction moire;
FIG. 8 is a schematic diagram illustrating an embodiment of a color space for performing a method of moire suppression; and
Fig. 9 is a flow chart illustrating an embodiment of a method of suppressing moire.
Detailed Description
The following embodiments of the present invention are described in terms of specific examples, and those skilled in the art will appreciate the advantages and effects of the present invention from the disclosure herein. The invention is capable of other and different embodiments and its several details are capable of modification and variation in various respects, all from the point of view and application, all without departing from the spirit of the present invention. The drawings of the present invention are merely schematic illustrations, and are not drawn to actual dimensions. The following embodiments will further illustrate the related art content of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
It will be understood that, although the terms "first," "second," "third," etc. may be used herein to describe various components or signals, these components or signals should not be limited by these terms. These terms are used primarily to distinguish one element from another element or signal from another signal. In addition, the term "or" as used herein shall include any one or combination of more of the associated listed items as the case may be.
According to the embodiments of the method for determining moire, the method for suppressing moire and the circuit system disclosed in the specification, in the embodiment of the method for determining moire, moire in different directions is detected mainly according to moire response values, that is, the positions where moire occurs are obtained by using the distribution characteristics of pixels in an image, then the moire characteristic comparison values are counted, the type is determined, and finally color noise reduction is performed on the pixels determined to be moire in the method for suppressing moire.
The types of moire can be roughly classified into horizontal and vertical moire, main diagonal and sub diagonal moire, and the like. For example, circuitry may analyze each pixel (or pixel for sampling) channel in an image one by one to determine if the pixel has a moire in the horizontal, vertical, or positive/negative diagonal directions, and still further perform suppression. Here, since the moire is characterized by repeated lines with high density, luminance characteristics such as horizontal, vertical, and diagonal lines can be used as conditions for determining the moire.
Referring first to fig. 1, which is a functional block diagram illustrating an embodiment of a circuit system implementing the moire judging and suppressing method, the circuit system may be a digital image processor (DIGITAL IMAGE processor) or implemented by a computer system, and main circuits of the circuit system include a processor and a memory, wherein the moire judging and suppressing method is implemented by the processor, and according to functions, the circuit system may include a color space converting unit 102, a moire response value calculating unit 103, a moire feature counting unit 104, a moire judging unit 105 and a moire suppressing unit 106 implemented by software or matched hardware, and a flow of the method for judging moire and a flow of the method for suppressing moire are described below, and referring to a flow of an embodiment of the method shown in fig. 2, and functions of each unit.
After receiving the original image 101 (step S201, fig. 2) through the circuitry shown in fig. 1, a color space converting unit 102 converts the image into a specific color space (step S203) capable of performing judgment and color moire suppression, such as YUV (luminance-chrominance-density) color space, RGB (red-green-blue) color space, etc., for an original image file (RAW) or a pixel value of a color space (color space), and particularly, any color space capable of obtaining pixel luminance information. The Y value of each pixel in the YUV color space represents a brightness value, and the RGB color space can be the average value of the three-color channel values of each pixel after color reproduction as the basis for judging brightness.
The circuit system can determine a detection window according to the hardware operation capability, and judge whether each pixel is a position where moire occurs pixel by pixel, wherein the method is that a plurality of key pixels for judging the moire type can be selected in the detection window before, and the distribution characteristics of the key pixels and the adjacent pixels in each region (corresponding to the size of the detection window) in the image are obtained by calculating each pixel one by one through the detection window. The moire response value calculation unit 103 in the circuit system may calculate the moire response values in the horizontal, vertical or diagonal directions one by using the brightness values of the pixels by applying the weight values of each pixel set in the detection window (step S205), and the moire response values in each direction may determine whether each pixel belongs to an edge pixel (edge pixel) conforming to the moire feature. Then, the moire feature statistics unit 104 in the circuit system obtains the moire feature relation between several key pixels for determining the moire direction and the adjacent pixels in each detection window, which may be the brightness value of the comparison pixel, and performs statistics on the moire feature comparison value of the adjacent pixels (step S207).
Next, by the moire judging unit 105 of the circuit system, the moire response value and the moire feature comparison value obtained in the above steps can be checked according to the threshold value set by the system to determine whether the current pixel is a part of the moire (step S209), and then the moire suppressing unit 106 performs color suppression on the pixel judged to be a part of the moire, wherein the color of the pixel in the range of the moire can be suppressed to be gray level, or different suppression magnification is set according to different degrees, and then the color of the suppressed pixel is gray level (step S211), and finally the result is output, that is, the output image 107 subjected to the moire suppression is output (step S213).
An embodiment of determining the moire direction in the method of determining moire shown in fig. 3 can be referred to as a drawing.
Fig. 3 shows a region of a 5x5 pixel array in an image, and the practical implementation can select an appropriate pixel array according to hardware resources, and this embodiment uses the Y value (brightness value) of a pixel in the YUV color space as a calculation basis. The pixel currently performing the judgment in the pixel array of 5×5 is Y (i, j), and this is taken as the origin of the region to label the adjacent pixels, for example, the horizontal pixel of the lower pixel Y (i, j) includes: y (i, j-2), Y (i, j-1), Y (i, j), Y (i, j+1), and Y (i, j+2); the vertical pixel includes: y (i-2, j), Y (i-1, j), Y (i, j), Y (i+1, j) and Y (i+2, j); the main diagonal (upper left right lower) pixel includes: y (i-2, j-2), Y (i-1, j-1), Y (i, j), Y (i+1, j+1) and Y (i+2, j+2).
Fig. 4A is a schematic diagram showing a pixel array with vertical moire, in which the central pixel is the current pixel 40, and the vertical moire is characterized by the fact that the brightness values of the pixels in the vertical direction are relatively close (threshold can be set to determine the degree of approach) compared with other directions, and the brightness values of the current pixel 40 and other neighboring pixels (left, right, upper left, lower left, upper right, lower right) should be relatively large (threshold can be set to determine the difference value) except for the pixels in the vertical direction, so this feature can be used to find the vertical moire.
Fig. 4B is a schematic diagram of a pixel array having a horizontal moire, where the central pixel is the current pixel 40', and similarly, in fig. 4B, the horizontal moire is characterized by a relatively close pixel brightness value in the horizontal direction, and the difference between the brightness values of the current pixel 40' and other neighboring pixels (up, down, upper left, lower left, upper right, lower right) is relatively large, so that the horizontal moire can be found by using this feature.
Embodiment one: moire in horizontal and vertical directions.
In combination with the above-mentioned features of the moire in the horizontal and vertical directions, as shown in fig. 5A to 5C, the method for determining the moire is to determine whether the moire in the horizontal or vertical direction exists by calculating the difference between the luminance values (e.g., Y values) of the current pixel 50 and the adjacent diagonal (diagonal) pixels (called key pixels). Fig. 5A uses the center pixel as the current pixel 50 and the difference in luminance value between the diagonal pixels (indicated by arrows) as the basis for determining horizontal or vertical moire. FIG. 5B is another representation of the luminance value differences between the key pixels in the 5x5 array and the diagonal pixels (as indicated by the arrows) are required as the basis for determining horizontal or vertical moire. FIG. 5C shows an example of a weight mask (mask) set for a key pixel and its neighboring pixels in the detection window, the weight mask is designed according to the type to be determined, and a higher weight value can be given to the key pixel when the moire response value is calculated, this embodiment is 4 and 1, the highest weight value 4 can be set for the current pixel 50, and the remaining key pixels are set as weight values 1 as coefficients of the algorithm; whereas the key pixel is given a lower weight value (in this embodiment, -2) to the diagonally adjacent pixels, thereby accentuating the spatial distribution characteristics of the image.
Referring to the pixel indicated in fig. 3 and fig. 5A to 5C, equation a shows that the horizontal or vertical moire response value of the specific region corresponding to the detection window is calculated for each pixel in the image with the detection window, equation a shows that the first half equation "4*Y (i, j) +y (i-2, j) +y (i, j+2) +y (i+2, j) +y (i, j-2))" is the sum of the luminance values of several key pixels in a certain image region, and in particular, may be multiplied by the weight value shown in fig. 5C; the second half of equation A, equation (2*Y (i-1, j-1) +2*Y (i-1, j+1) +2*Y (i+1, j+1) +2*Y (i+1, j-1)), is the sum of luminance values of diagonally adjacent pixels of the calculated key pixel (multiplied by the weight value shown in FIG. 5C). The luminance value gradient (gradient) in the pixel region is obtained by subtracting the front and back formulas of the formula A and taking the absolute value, when the luminance value gradient of the whole image is calculated, the larger the difference (absolute value) is, the more the horizontal or vertical Moire in the image is highlighted, otherwise, no obvious Moire is indicated, the difference is indicated as a Moire response value (moire_ HVEdge) in the horizontal and vertical directions, namely, the edge characteristic of the pixel is obtained, so that whether the pixel has the Moire feature or not is judged, and the phenomenon that the Moire is generated when the sampling frequency of the pixel is consistent with or close to the spatial frequency of the line is confirmed.
Moire_HVEdge＝|(4*Y(i,j)+Y(i-2,j)+Y(i,j+2)+Y(i+2,j)+Y(i,j-2))-(2*Y(i-1,j-1)+2*Y(i-1,j+1)+2*Y(i+1,j+1)+2*Y(i+1,j-1))|( Formula A
And then, utilizing a detection window to compare brightness values of a plurality of key pixels and corresponding adjacent pixels in a pixel area where each pixel is positioned one by one, and counting the brightness values to detect edges and judge the edges as moire. Equation B and equation C represent statistical horizontal or vertical moire feature comparison values. According to the pixel brightness values shown in fig. 1, if the current pixel brightness value Y (i, j) is a relatively high brightness value, as shown in formula B, wherein KHV represents the difference between the pixel values set by the user, the difference between the brightness values of the key pixels (Y (i, j), Y (i-2, j), Y (i, j+2), Y (i+2, j), Y (i, j-2)) and the neighboring key pixels in the horizontal and vertical directions is larger (the brightness value is at least larger than KHV), which can be determined as the threshold of moire. Wherein the luminance value comparison and statistics may be performed only for pixels confirmed to be part of moire by the moire response value.
Equation B:
Moire_HVCMP1＝(Y(i,j)>Y(i-1,j-1)+KHV)
Moire_HVCMP2＝(Y(i,j)>Y(i-1,j+1)+KHV)
Moire_HVCMP3＝(Y(i,j)>Y(i+1,j+1)+KHV)
Moire_HVCMP4＝(Y(i,j)>Y(i+1,j-1)+KHV)
Moire_HVCMP5＝(Y(i-2,j)>Y(i-1,j-1)+KHV)
Moire_HVCMP6＝(Y(i-2,j)>Y(i-1,j+1)+KHV)
Moire_HVCMP7＝(Y(i,j+2)>Y(i-1,j+1)+KHV)
Moire_HVCMP8＝(Y(i,j+2)>Y(i+1,j+1)+KHV)
Moire_HVCMP9＝(Y(i+2,j)>Y(i+1,j+1)+KHV)
Moire_HVCMP10＝(Y(i+2,j)>Y(i+1,j-1)+KHV)
Moire_HVCMP11＝(Y(i,j-2)>Y(i-1,j-1)+KHV)
Moire_HVCMP12＝(Y(i,j-2)>Y(i+1,j-1)+KHV)
If the luminance value Y (i, j) of the lower pixel is a relatively low luminance value, as shown in formula C, KHV is used as a threshold for confirming that the luminance value difference between the key pixels (Y (i, j), Y (i-2, j), Y (i+2, j), Y (i, j-2)) and the neighboring pixels in the horizontal and vertical directions is larger than (increasing the luminance difference threshold with KHV).
Equation C:
Moire_HV’CMP1＝(Y(i,j)<Y(i-1,j-1)-KHV)
Moire_HV’CMP2＝(Y(i,j)<Y(i-1,j+1)-KHV)
Moire_HV’CMP3＝(Y(i,j)<Y(i+1,j+1)-KHV)
Moire_HV’CMP4＝(Y(i,j)<Y(i+1,j-1)-KHV)
Moire_HV’CMP5＝(Y(i-2,j)<Y(i-1,j-1)-KHV)
Moire_HV’CMP6＝(Y(i-2,j)<Y(i-1,j+1)-KHV)
Moire_HV’CMP7＝(Y(i,j+2)<Y(i-1,j+1)-KHV)
Moire_HV’CMP8＝(Y(i,j+2)<Y(i+1,j+1)-KHV)
Moire_HV’CMP9＝(Y(i+2,j)<Y(i+1,j+1)-KHV)
Moire_HV’CMP10＝(Y(i+2,j)<Y(i+1,j-1)-KHV)
Moire_HV’CMP11＝(Y(i,j-2)<Y(i-1,j-1)-KHV)
Moire_HV’CMP12＝(Y(i,j-2)<Y(i+1,j-1)-KHV)
And comparing the statistics of the horizontal moire characteristic and the vertical moire characteristic obtained by the formula B and the formula C, for example, comparing the statistics of the brightness value Y (i, j) of the current pixel with the statistics of the brightness value Y (i, j) of the current pixel to judge whether the brightness of the current pixel is high or low relative to the adjacent pixels.
Formula D:
Embodiment two: the main diagonal direction mole lines.
For the main diagonal direction type, the characteristics of the diagonal direction moire are integrated, as shown in fig. 6A to 6C, in which a 5x5 pixel array is taken as an example, as shown in fig. 6A, the central pixel is the current pixel 60, and the method for judging the moire judges whether the moire has the main diagonal direction by calculating the difference value of the luminance values (such as Y values) of the current pixel 60 and the horizontal and vertical adjacent pixels, and the difference value of the luminance values between the current pixel 60 and the horizontal and vertical pixels is used as the basis for judging the moire of the main diagonal direction, as shown by the arrow in the figure. FIG. 6B is a schematic diagram of another embodiment, in which the difference in luminance values between several key pixels in the 5×5 pixel array and their horizontal and vertical neighboring pixels (as indicated by arrows) is used as a basis for determining the moire of the main diagonal. FIG. 6C illustrates an example of a weight mask (mask) showing that key pixels are given higher weight values when calculating the moire response value, in this embodiment 4 and 1, when the current pixel 60 may be provided with the highest weight value of 4, the remaining key pixels are set to weight value of 1; whereas pixels in the horizontal and vertical directions of the key pixels are given lower weight values (in this embodiment, -2), so that the spatial distribution characteristics of the image can be emphasized.
Referring to the pixels indicated in fig. 3 and fig. 6A to 6C, the equation E is a main diagonal moire response value of a specific region corresponding to a detection window calculated for each pixel in an image by the detection window, and similarly, the equation E shows that the first half equation in absolute value (4*Y (i, j) +y (i-1, j+1) +y (i-2, j+2) +y (i+1, j-1) +y (i+2, j-2)) is a sum of brightness values of key pixels in a certain image region, and in particular, may be multiplied by a weight value shown in fig. 6C; the second half of equation E, "2*Y (i-2, j) +2*Y (i, j+2) +2*Y (i+2, j) +2*Y (i, j-2)), is the sum of the luminance values of the neighboring pixels in the horizontal and vertical directions of the key pixel (e.g., the current pixel Y (i, j)), which can be multiplied by the weight value shown in FIG. 6C. Subtracting the front and back formulas of the formula E and taking the absolute value to obtain the brightness value gradient in the pixel area, and once the brightness value gradient of the whole image is calculated, the larger the difference (absolute value) is, the more the main diagonal moire in the image is highlighted; otherwise, no apparent moire is indicated. This difference is the Moire response value (Moire DIAG POSEdge) in the main diagonal direction, and is used to determine whether the Moire feature is present by obtaining the edge characteristics of the pixels.
Equation E:
Moire_DIAG_POSEdge＝
|(4*Y(i,j)+Y(i-1,j+1)+Y(i-2,j+2)+Y(i+1,j-1)+Y(i+2,j-2))-(2*Y(i-2,j)+2*Y(i,j+2)+2*Y(i+2,j)+2*Y(i,j-2))|
Similarly, the brightness values of a plurality of key pixels and corresponding adjacent pixels in the pixel region where the pixels are compared one by one are counted by utilizing the detection window, so as to detect the edge characteristics and judge the edge characteristics as moire. Equation F and equation G represent the comparison of the mole pattern characteristics of the statistical principal diagonal. According to the pixel brightness values shown in fig. 1, if the current pixel brightness value Y (i, j) is a relatively high brightness value, as shown in formula F, where KD represents the pixel value difference set by the user, the difference between the brightness values of the key pixels (Y (i, j), Y (i-2, j-1), Y (i-1, j-2), Y (i+1, j+2), Y (i+2, j+1)) and the neighboring pixels in the main diagonal direction is larger (the brightness value is at least larger than KD), which can be determined as the moire threshold. Wherein the luminance value comparison and statistics may be performed only for pixels confirmed to be part of moire by the moire response value.
Equation F:
Moire_DIAG_POS CMP1＝(Y(i,j)>Y(i-2,j)+KD)
Moire_DIAG_POS CMP2＝(Y(i,j)>Y(i,j+2)+KD)
Moire_DIAG_POS CMP3＝(Y(i,j)>Y(i+2,j)+KD)
Moire_DIAG_POS CMP4＝(Y(i,j)>Y(i,j-2)+KD)
Moire_DIAG_POS CMP5＝(Y(i-2,j-1)>Y(i-2,j)+KD)
Moire_DIAG_POS CMP6＝(Y(i-2,j-1)>Y(i-1,j-1)+KD)
Moire_DIAG_POS CMP7＝(Y(i-1,j-2)>Y(i-1,j-1)+KD)
Moire_DIAG_POS CMP8＝(Y(i-1,j-2)>Y(i,j-2)+KD)
Moire_DIAG_POS CMP9＝(Y(i+1,j+2)>Y(i,j+2)+KD)
Moire_DIAG_POS CMP10＝(Y(i+1,j+2)>Y(i+1,j+1)+KD)
Moire_DIAG_POS CMP11＝(Y(i+2,j+1)>Y(i+2,j)+KD)
Moire_DIAG_POS CMP12＝(Y(i+2,j+1)>Y(i+1,j+1)+KD)
If the luminance value Y (i, j) of the lower pixel is a relatively low luminance value, as shown in formula G, KD is also used as a threshold for determining that the difference between the luminance value of the key pixel and the luminance value of the neighboring pixel in the main diagonal direction is greater (increasing the luminance difference threshold by KD).
Equation G:
Moire_DIAG_POS’CMP1＝(Y(i,j)<Y(i-2,j)-KD)
Moire_DIAG_POS’CMP2＝(Y(i,j)<Y(i,j+2)-KD)
Moire_DIAG_POS’CMP3＝(Y(i,j)<Y(i+2,j)-KD)
Moire_DIAG_POS’CMP4＝(Y(i,j)<Y(i,j-2)-KD)
Moire_DIAG_POS’CMP5＝(Y(i-2,j-1)<Y(i-2,j)-KD)
Moire_DIAG_POS’CMP6＝(Y(i-2,j-1)<Y(i-1,j-1)-KD)
Moire_DIAG_POS’CMP7＝(Y(i-1,j-2)<Y(i-1,j-1)-KD)
Moire_DIAG_POS’CMP8＝(Y(i-1,j-2)<Y(i,j-2)-KD)
Moire_DIAG_POS’CMP9＝(Y(i+1,j+2)<Y(i,j+2)-KD)
Moire_DIAG_POS’CMP10＝(Y(i+1,j+2)<Y(i+1,j+1)-KD)
Moire_DIAG_POS’CMP11＝(Y(i+2,j+1)<Y(i+2,j)-KD)
Moire_DIAG_POS’CMP12＝(Y(i+2,j+1)<Y(i+1,j+1)-KD)
And comparing the statistics results of the main diagonal moire features obtained by the formula F and the formula G, for example, the formula H, and comparing the statistics results of the brightness value Y (i, j) of the current pixel with the statistics results of relatively high and low, so as to judge that the current pixel is a pixel with relatively high or low brightness.
Formula H:
embodiment III: mole lines in the direction of the minor diagonal.
For the type of the minor diagonal direction, as shown in fig. 7A to 7C, taking a 5x5 pixel array as an example, as shown in fig. 7A, the center pixel is the current pixel 70, and the method for determining the moire determines whether the moire has the minor diagonal direction by calculating the difference between the luminance values (e.g., Y values) of the current pixel 70 and the horizontal and vertical neighboring pixels, as shown by the arrow in the figure. FIG. 7B is a schematic illustration showing the difference in luminance values between a plurality of key pixels in a 5x5 pixel array and their horizontal and vertical neighboring pixels (as indicated by arrows) as a basis for determining the mole marks of the minor diagonal lines. FIG. 7C illustrates an example of a weight mask (mask) set forth for determining the next diagonal moire, wherein the key pixels are given higher weight values when the moire response value is calculated, in this embodiment 4 and 1, the lower pixel 70 may be provided with the highest weight value of 4, and the remaining key pixels are set to weight value 1; whereas pixels in the horizontal and vertical directions of the key pixels are given lower weight values (in this embodiment, -2), so that the spatial distribution characteristics of the image can be emphasized.
Referring to the pixel indicated in fig. 3 and fig. 7A to 7C, the equation I is a second diagonal moire response value of a specific region corresponding to the detection window calculated for each pixel in the image by the detection window, and similarly, the equation I shows the first half equation in absolute value (4*Y (I, j) +y (I-1, j-1) +y (I-2, j-2) +y (i+1, j+1) +y (i+2, j+2)) @ as the sum of brightness values of the key several pixels in the image region, in particular, the sum of brightness values can be multiplied by the weight value shown in fig. 7C; the second half of equation I, "2*Y (I-2, j) +2*Y (I, j+2) +2*Y (i+2, j) +2*Y (I, j-2)), is the sum of the luminance values of the neighboring pixels in the horizontal and vertical directions of the key pixel (e.g., the current pixel Y (I, j)), which can be multiplied by the weight value shown in fig. 7C. Subtracting the front and back formulas of the formula I and taking the absolute value to obtain the brightness value gradient in the pixel area, once the brightness value gradient of the whole image is calculated, the larger the difference (absolute value) is, the more the secondary diagonal moire in the image is highlighted; otherwise, no apparent moire is indicated. This difference is the Moire response value (Moire DIAG POSEdge) in the minor diagonal direction, and is used to determine whether the Moire feature is present by taking the edge characteristics of the pixel.
Formula I:
Moire_DIAG_NEGEdge＝
|(4*Y(i,j)+Y(i-1,j-1)+Y(i-2,j-2)+Y(i+1,j+1)+Y(i+2,j+2))-(2*Y(i-2,j)+2*Y(i,j+2)+2*Y(i+2,j)+2*Y(i,j-2))|
Similarly, the brightness values of a plurality of key pixels and corresponding adjacent pixels in the pixel region where the pixels are compared one by one are counted by utilizing the detection window, so as to detect the edge characteristics and judge the edge characteristics as moire. Equation J and equation K represent the statistical minor diagonal moire feature comparison values. According to the pixel brightness values indicated in fig. 1, if the current pixel brightness value Y (i, J) is a relatively high brightness value, as shown in formula J, KD represents the pixel value difference set by the user, and the difference between the brightness values of the key pixel and the adjacent pixels in the direction of the minor diagonal is greater than a threshold value that can be determined as moire according to the actual ambient light source. Wherein the luminance value comparison and statistics may be performed only for pixels confirmed to be part of moire by the moire response value.
Formula J:
Moire_DIAG_NEGCMP1＝(Y(i,j)>Y(i-2,j)+KD)
Moire_DIAG_NEGCMP2＝(Y(i,j)>Y(i,j+2)+KD)
Moire_DIAG_NEGCMP3＝(Y(i,j)>Y(i+2,j)+KD)
Moire_DIAG_NEGCMP4＝(Y(i,j)>Y(i,j-2)+KD)
Moire_DIAG_NEGCMP5＝(Y(i-2,j+1)>Y(i-2,j)+KD)
Moire_DIAG_NEGCMP6＝(Y(i-2,j+1)>Y(i-1,j+1)+KD)
Moire_DIAG_NEGCMP7＝(Y(i-1,j+2)>Y(i-1,j+1)+KD)
Moire_DIAG_NEGCMP8＝(Y(i-1,j+2)>Y(i,j+2)+KD)
Moire_DIAG_NEGCMP9＝(Y(i+1,j-2)>Y(i,j-2)+KD)
Moire_DIAG_NEGCMP10＝(Y(i+1,j-2)>Y(i+1,j-1)+KD)
Moire_DIAG_NEGCMP11＝(Y(i+2,j-1)>Y(i+1,j-1)+KD)
Moire_DIAG_NEGCMP12＝(Y(i+2,j-1)>Y(i+2,j)+KD)
if the luminance value Y (i, j) of the lower pixel is a relatively low luminance value, as shown in formula K, KD is also used as a threshold for determining that the difference between the luminance value of the critical pixel and the luminance value of the neighboring pixel in the minor diagonal direction is greater (increasing the luminance difference threshold by KD).
Equation K:
Moire_DIAG_NEG’CMP1＝(Y(i,j)<Y(i-2,j)-KD)
Moire_DIAG_NEG’CMP2＝(Y(i,j)<Y(i,j+2)-KD)
Moire_DIAG_NEG’CMP3＝(Y(i,j)<Y(i+2,j)-KD)
Moire_DIAG_NEG’CMP4＝(Y(i,j)<Y(i,j-2)-KD)
Moire_DIAG_NEG’CMP5＝(Y(i-2,j+1)<Y(i-2,j)-KD)
Moire_DIAG_NEG’CMP6＝(Y(i-2,j+1)<Y(i-1,j+1)-KD)
Moire_DIAG_NEG’CMP7＝(Y(i-1,j+2)<Y(i-1,j+1)-KD)
Moire_DIAG_NEG’CMP8＝(Y(i-1,j+2)<Y(i,j+2)-KD)
Moire_DIAG_NEG’CMP9＝(Y(i+1,j-2)<Y(i,j-2)-KD)
Moire_DIAG_NEG’CMP10＝(Y(i+1,j-2)<Y(i+1,j-1)-KD)
Moire_DIAG_NEG’CMP11＝(Y(i+2,j-1)<Y(i+1,j-1)-KD)
Moire_DIAG_NEG’CMP12＝(Y(i+2,j-1)<Y(i+2,j)-KD)
and then, comparing the statistics results of the secondary diagonal moire features obtained by the formula J and the formula K, such as the formula L, and comparing the statistics results of the brightness value Y (i, J) of the current pixel with the statistics results of relatively high and low, wherein the aim is to judge that the current pixel is a pixel with relatively high or low brightness.
Formula L:
According to the above embodiment, in the method for determining moire, the horizontal vertical, positive/negative diagonal moire response value is calculated, and then the luminance information of the next pixel and the neighboring pixels in the horizontal vertical, positive/negative diagonal directions are compared, and the luminance characteristics of the next pixel compared with the neighboring pixels can be determined by counting the comparison result. The method can determine whether the current pixel is moire according to a threshold value set by a system and a moire response value and a statistical result, including determining the position and the type of the moire in the image.
According to one embodiment, when the moire response value is greater than the first threshold value, it can be determined that the current pixel has a definite brightness change from its neighboring pixels, and thus it can be determined that the edge pixel of the image, that is, the pixel has a feature such as a bright-dark interval of moire in the vicinity of the pixel; conversely, if the moire response value is not greater than the first threshold value, it cannot be concluded that the current pixel has the moire characteristic. When the moire characteristic comparison value is greater than the second threshold value, the characteristic that the current pixel is relatively bright or relatively dark is judged, and in combination with the judgment that the moire response value is greater than the first threshold value, the current pixel can be determined to be part of the moire.
After determining the moire in the image, the circuitry may perform color noise reduction on the pixel determined as the moire, for example, performing color suppression on the pixel determined as the moire in the YUV color space, as shown in fig. 8, which is a UV (chromaticity-concentration) plane at y=128 in the YUV color space. The pixels determined as moire are mapped in the chromaticity-density plane under the YUV color space, the closer to the coordinate center 80, the lower the color saturation, the closer to the gray scale, and the farther from the coordinate center 80, the higher the color saturation, and represent different colors according to different quadrants, respectively.
According to the color U/V values of the moire pixels located at the coordinate positions of the color space, the chromaticity-density plane may be divided into two or three regions to be respectively subjected to different color processes, as shown in fig. 8, the central region represents a color suppression range 801, the colors of pixels falling within this color suppression range 801 are suppressed to gray scale, and then an image with suppressed color moire is outputted.
According to one embodiment, the color-density plane may have three regions, where a color suppression progressive range 803 is represented between a region outlined by a dotted line and the color suppression range 801, and pixel colors within the color suppression progressive range 803 between the color suppression range 801 and the dotted line are adjusted to set a suppression magnification according to a distance from the coordinate center 80, so that color suppression is performed according to the suppression magnification, for example, different gray scale levels are applied. The suppression ratio can be changed linearly or nonlinearly, and the colors outside the virtual line of the color suppression progressive range 803 are not affected, so as to maintain the original U/V value.
According to one embodiment, the color suppression area 801 is a movable rectangular area, but still needs to cover the coordinate center 80, and the rectangular area can be flexibly moved to cover the color to be suppressed in different scene applications or according to the preference of the user. The color suppression formula is as formula M:
cout= (Cin-128) × (1-support_rate) +128 (formula M)
Wherein Cin is an input U or V value, cout is a corresponding output U or V value, and supp_rate is a suppression ratio between 0 and 1. The suppression ratio is calculated in the color suppression progressive range 803 according to the distance from the coordinate center 80, the suppression ratio is gradually decreased as the suppression ratio is further from the center, the suppression ratio from 0 to 1 can be calculated by Interpolation (filtration), filtering (Filter) and other methods, the value 128 in the formula M is a value ranging from 0 to 255 according to the U and V values in the YUV color space in this example, the conversion is performed to the coordinate plane, the actual implementation can be modified according to the actual requirement, and the suppression ratio calculation is not limited to the listed method.
According to the above embodiments, the process of the moire judging method and the moire suppressing method running in the circuit system can firstly obtain the brightness information of each pixel in a color space in the received image, select a detection range, obtain the spatial distribution characteristics according to the brightness relationship of the pixels, obtain the edge characteristics of the pixels, further judge whether the moire is present or not, judge whether the moire is horizontal, vertical or the type of positive/negative diagonal, and then count the characteristic comparison value of the moire of a specific type, so as to determine whether the pixel is part of the moire, and then execute color moire suppression on the pixel judged to be the moire.
In the circuit system, referring to fig. 9, in the flow of moire judgment and suppression, in step S901, after the circuit system receives an image, judgment of moire is made on pixels one by one, and a relationship between a current pixel and its neighboring pixel value (especially, for example, a brightness value) is obtained according to a detection window to obtain the characteristic of spatial distribution of the image. According to the above embodiment, when the moire is set in the horizontal or vertical direction, a key pixel in a detection window is selected, a weight value is given, and a response value of the moire is calculated, that is, a brightness difference value between the key pixel and an adjacent pixel is used, and after a first threshold is compared, the first threshold is used as a basis for determining the moire direction.
In step S903, after processing each pixel one by one, whether the image has a moire pattern in the horizontal or vertical direction is determined according to the above, if it is determined that the image has a moire pattern in the horizontal or vertical direction, color suppression is performed for the pixel having a moire pattern position (step S907), and the image is output after the completion (step S909); otherwise, the flow continues to step S905, where it is determined whether the image has a diagonal mole pattern, and similarly, if it is determined that the image has a diagonal mole pattern, then, as in step S907, color suppression is performed for the mole pattern position therein, and the image is output after completion (step S909); on the other hand, if no diagonal moire is found in the image, indicating that no clear moire is found in the image, the image is directly output (step S909). Thus, the method and the circuit system for judging and suppressing the moire disclosed in the specification are realized.
The foregoing disclosure is only illustrative of the preferred embodiments of the present invention and is not to be construed as limiting the scope of the invention, which is defined by the appended claims and their equivalents.
[ Symbolic description ]
Original image 101
Color space conversion unit 102
Moire response value calculation unit 103
Moire feature statistics unit 104
Moire judging unit 105
Moire suppression unit 106
Output image 107
Lower pixels 40,40',50,60,70
Coordinate center 80
Color suppression Range 801
Color suppression progressive range 803
Step S201-S213 judgment and Moire suppression method flow
Step S901-S909 judgment and mole pattern suppression method flow
Claims (9)
1. A method of determining moire comprising:
Obtaining brightness information of a plurality of pixels in an image;
a detection window is arranged, and a plurality of key pixels for judging the mole pattern type are selected from the detection window;
for each pixel, calculating a moire response value of the plurality of key pixels and a plurality of adjacent pixels corresponding to the key pixels respectively through the detection window, wherein the moire response value is used for judging whether the image has moire characteristics or not;
Comparing brightness information of the plurality of key pixels and a plurality of corresponding adjacent pixels by using the detection window for each pixel, and counting comparison results to judge brightness characteristics of each pixel; and
Confirming the position and type of the moire in the image according to the moire response value and the statistical result,
In the step of calculating the moire response value, a weight mask is set in the detection window, and the plurality of key pixels and the corresponding plurality of adjacent pixels are multiplied by weight values respectively to calculate the moire response value.
2. The method according to claim 1, wherein the luminance information of the plurality of pixels is a luminance value in a luminance-chrominance-density color space or an average value of three color channel values in a red-green-blue color space.
3. The method of claim 2, wherein a color space conversion is performed on the image to convert to the luminance-chrominance-density color space or the red-green-blue color space when the image is acquired.
4. The method according to claim 1, wherein in the step of calculating the moire response value, the weight mask is designed according to the type of moire to be judged, higher weight values are given to the plurality of key pixels, and lower weight values are given to the plurality of adjacent pixels.
5. The method according to claim 4, wherein the moire response value calculated for each pixel is compared with a first threshold value to obtain a brightness change between the pixel and its neighboring pixels, and further determining whether the image has moire features.
6. The method of claim 1, wherein a second threshold is introduced to verify the brightness characteristics of each pixel when comparing the brightness information of the plurality of key pixels with the brightness information of the plurality of neighboring pixels respectively corresponding to the plurality of key pixels.
7. The method according to any one of claims 1 to 6, wherein the type of moire is a moire in a horizontal and vertical direction, a moire in a main diagonal direction, or a moire in a sub diagonal direction.
8. A method of inhibiting moire comprising:
obtaining an image, converting the image into a brightness-chromaticity-concentration color space, and obtaining brightness values of a plurality of pixels in the image;
A detection window is arranged, and a plurality of key pixels used for judging the mole pattern type are selected from the detection window;
calculating a moire response value of the plurality of key pixels and a plurality of adjacent pixels corresponding to each pixel through the detection window, wherein the moire response value is used for judging whether the image has moire characteristics or not;
In the step of calculating the moire response value, a weight mask is set in the detection window, and the plurality of key pixels and the corresponding plurality of adjacent pixels are multiplied by weight values respectively to calculate the moire response value;
comparing brightness values of the plurality of key pixels and a plurality of corresponding adjacent pixels by using the detection window for each pixel, and counting comparison results to judge brightness characteristics of each pixel;
confirming the positions and types of the moire patterns in the image according to the moire response values and the statistical results;
Color noise reduction is performed on a plurality of pixels judged to be moire, wherein:
mapping a plurality of pixels determined as moire on a chrominance-density plane of the luminance-chrominance-density color space; and
And suppressing the pixel color in a color suppression range in the chromaticity-concentration plane to gray level.
9. A circuit system, comprising:
A processor and a memory, wherein the processor performs a moire determining method comprising:
obtaining an image, converting the image into a brightness-chromaticity-concentration color space, and obtaining brightness values of a plurality of pixels in the image;
A detection window is arranged, and a plurality of key pixels used for judging the mole pattern type are selected from the detection window;
calculating a moire response value of the plurality of key pixels and a plurality of adjacent pixels corresponding to each pixel through the detection window, wherein the moire response value is used for judging whether the image has moire characteristics or not;
In the step of calculating the moire response value, a weight mask is set in the detection window, and the plurality of key pixels and the corresponding plurality of adjacent pixels are multiplied by weight values respectively to calculate the moire response value;
Comparing brightness values of the plurality of key pixels and a plurality of corresponding adjacent pixels by using the detection window for each pixel, and counting comparison results to judge brightness characteristics of each pixel; and
And confirming the positions and types of the moire in the image according to the moire response value and the statistical result so as to perform color noise reduction on the pixels judged to be the moire.
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