CN113129389A

CN113129389A - Moire pattern judging method, Moire pattern inhibiting method and circuit system

Info

Publication number: CN113129389A
Application number: CN201911389012.7A
Authority: CN
Inventors: 萧晶如; 黄文聪
Original assignee: Realtek Semiconductor Corp
Current assignee: Realtek Semiconductor Corp
Priority date: 2019-12-30
Filing date: 2019-12-30
Publication date: 2021-07-16

Abstract

A method for judging and suppressing Moire pattern includes obtaining brightness values of multiple pixels in image, selecting multiple key pixels for judging Moire pattern type in detection window, calculating Moire pattern response value of multiple key pixels and multiple adjacent pixels through detection window for each pixel, comparing brightness values of key pixels and adjacent pixels by using detection window, counting comparison result for judging brightness characteristic of each pixel and confirming position and type of Moire pattern in image according to Moire pattern response value and result of statistics. Then, color noise reduction is performed on the plurality of pixels determined as the moire.

Description

Moire pattern judging method, Moire pattern inhibiting method and circuit system

Technical Field

The present invention relates to moire judgment technology, and more particularly, to a method for detecting moire fringes in different directions, a method for counting a comparison value of moire characteristics to judge moire fringes, a method for suppressing moire, and a circuit system for implementing the method.

Background

Among the common imaging defects in digital images, moire Pattern (moire Pattern) is a kind of moire Pattern, and the moire Pattern is generally formed because when a photosensitive element (such as a CCD or a CMOS) in an image sensor acquires image data, such as a digital camera, a digital video camera, or a scanner, the processed image is subjected to high frequency interference, and color and irregular shape stripes, called moire patterns, appear on the image.

In addition, when an object with dense grains (such as textile, lines with high repeatability, a display screen and the like) is shot, if the pixel sampling frequency of the photosensitive assembly is close to the spatial frequency of the grains on the object, low-frequency grains can be generated on an image, and meanwhile, due to the fact that a Bayer Filter (Bayer Filter) is used, the sampling rate of red, green and blue visible light is different, color noise is often accompanied on the Moire grains, and the result actually seen by human eyes is not met.

In order to solve the moire phenomenon, an optical Low-Pass Filter (Low-Pass Filter) is added to the camera during the manufacture of the camera or the lens, which helps to reduce the moire phenomenon, but loses part of the image details. Another solution is to perform post-processing in an Image Signal Processor (ISP), so that a place with low brightness variation and high color variation of a pixel can be determined as a position where moire occurs, and color compensation can be performed according to neighboring pixels, but there is a problem that saturation (saturation) may be reduced.

Thus, the method disclosed in the prior art may not be able to detect moire accurately, if there is misjudgment, the color quality of the image may be reduced, and the mechanism of color compensation may be limited by hardware limitations and may not be able to completely eliminate moire.

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 purpose is to process moire (moire Pattern) in a digital image by utilizing an image processing technology, including detecting the position of the moire, and one purpose is to reduce color noise of the position where the moire occurs and enable an imaging result to be more in line with the visual perception of human eyes.

According to an embodiment of the method for determining moire, luminance information of a plurality of pixels in an image is obtained, such as a luminance value in a YUV (luminance-chrominance-density) color space or an average value of three color channel values in an RGB (red-green-blue) color space, a detection window is provided, a plurality of key pixels for determining moire type are selected in the detection window, and a moire response value of the plurality of key pixels and a plurality of corresponding neighboring pixels in the detection window is calculated one by one for each pixel, which can be used to determine whether the image has moire features.

Then, aiming at each pixel, comparing the brightness values of a plurality of key pixels and a plurality of corresponding adjacent pixels by using a detection window, and counting the comparison result to judge the brightness characteristic of each pixel, so that the position and the type of the moire in the image can be confirmed according to the moire response value and the statistical result.

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 type of moire 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 to calculate the moire response value.

Furthermore, the moire response value calculated for each pixel can be compared with the first threshold value to obtain the brightness change of the pixel and the adjacent pixels, and then whether the image has moire features or not can be further judged. Moreover, when comparing the luminance information of the plurality of key pixels with the luminance information of the plurality of corresponding adjacent pixels, a second threshold value is introduced to confirm the luminance characteristics of each pixel.

The moire patterns are in horizontal and vertical directions, major diagonal directions or minor diagonal directions.

Furthermore, the color moire suppression can be performed on the relevant pixels judged to be moire, the color moire suppression method comprises the steps of mapping a plurality of pixels judged to be moire on a chroma-concentration plane of a brightness-chroma-concentration color space, and then suppressing the pixel color in a color suppression range in the chroma-concentration plane into a gray scale, further, the chroma-concentration plane further distinguishes a color suppression progressive range, a suppression multiplying factor is set for the distance between the pixel color in the color suppression progressive range and a coordinate center of the chroma-concentration plane, and in the color suppression progressive range, the color suppression can be performed according to the suppression multiplying factor.

According to one embodiment of the circuit system, the digital image processor may be a digital image processor, wherein the moire determining method and the moire suppressing method are performed.

For a better understanding of the features and technical content of the present invention, reference should be made to the following detailed description of the invention and accompanying drawings, which are provided for purposes of illustration and description only and are not intended to limit the invention.

Drawings

FIG. 1 is a functional block diagram illustrating one embodiment of circuitry for implementing the method for determining and suppressing moir é;

FIG. 2 is a flow chart illustrating an embodiment of a method of determining and suppressing moir é;

FIG. 3 is a schematic view showing an example of judging a moire direction in the method of judging moire;

FIGS. 4A and 4B are schematic diagrams showing horizontal and vertical moir patterns, respectively;

FIGS. 5A to 5C are schematic views showing a method of judging horizontal and vertical moire;

FIGS. 6A to 6C are schematic views showing a method of judging a main diagonal moir é;

FIGS. 7A to 7C are schematic views showing a method of judging sub-diagonal moir é;

FIG. 8 is a schematic diagram illustrating an embodiment of a color space in which a method of suppressing moir é is performed; and

FIG. 9 is a flow chart illustrating an embodiment of a method of suppressing moir é.

Detailed Description

The following is a description of embodiments of the present invention with reference to specific embodiments, and those skilled in the art will understand the advantages and effects of the present invention from the disclosure of the present specification. The invention is capable of other and different embodiments and its several details are capable of modifications and various changes in detail, all without departing from the spirit and scope of the present invention. The drawings of the present invention are for illustrative purposes only and are not drawn to scale. The following embodiments will further explain the related art 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 from one signal to another signal. In addition, the term "or" as used herein should be taken to include any one or combination of more of the associated listed items as the case may be.

According to the embodiments of the moire judging method, the moire inhibiting method and the circuit system disclosed in the specification, in the moire judging method embodiment, moire in different directions is mainly detected according to moire response values, namely, a moire occurrence place is obtained by utilizing the distribution characteristics of pixels in an image, then, moire feature comparison values are counted, the type is determined, and finally, color noise reduction is performed on the pixels judged as moire in the moire inhibiting method.

The moire pattern types can be roughly classified into horizontal and vertical moire patterns, major diagonal and minor diagonal moire patterns, and the like. For example, the circuitry may analyze each pixel (or pixel sampled) channel in the image one by one to determine whether the pixel has moire in the horizontal, vertical, or positive/negative diagonal directions, and then further perform the suppression. It is noted that since the moire is characterized by repeated and highly dense lines, the luminance characteristics such as horizontal, vertical, and diagonal lines can be used as the conditions for determining the moire.

Referring first to fig. 1, it is a functional block diagram showing an embodiment of a circuit system for implementing the method for determining and suppressing moire fringes, where the circuit system may be a digital image processor (digital image processor) or a computer system, and the main circuit of the circuit system includes a processor and a memory, where the method for determining and suppressing moire fringes is run by the processor, and according to the functions, the circuit system may include a color space conversion unit 102, a moire response value calculation unit 103, a moire feature statistics unit 104, a moire determination unit 105, and a moire suppression unit 106, which are implemented by software or hardware, and the following describes the flow of the method for determining moire and the method for suppressing moire by the circuit system, and refer to the flow of the method embodiment shown in fig. 2 and the functions of each unit.

After receiving the original image 101 (step S201, fig. 2) by the circuit system shown in fig. 1, which may be an original image file (RAW) or a pixel value of a certain color space (color space), the 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 a YUV (luminance-chrominance-density) color space, an RGB (red-green-blue) color space, and the like, 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 used as a basis for judging brightness for the average value of three-color channel values of each pixel after color reduction.

The circuit system can determine a detection window according to the hardware operational capability, and judge whether each pixel is the position of the moire fringe or not pixel by pixel, wherein the method can select a plurality of key pixels for judging the moire fringe type in the detection window, and calculate one by one for each pixel through the detection window to obtain the distribution characteristics of the key pixels and the adjacent pixels in each area (corresponding to the size of the detection window) in the image to obtain the position of the moire fringe. In an embodiment, the moire response value calculating unit 103 in the circuit system applies the weight values of the pixels set in the detection window, and calculates the moire response values in the horizontal, vertical or diagonal directions one by one using the brightness values of the pixels (step S205), and the moire response values in each direction can 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 relationship between several key pixels for determining moire direction and adjacent pixels in each detection window, which may be the brightness value of the comparison pixel, and performs statistics on the moire feature comparison values of the adjacent pixels (step S207).

Then, the moire judging unit 105 of the circuit system can check the moire response value and the moire feature comparison value obtained in the above steps according to the threshold set by the system to determine whether the current pixel belongs to a part of moire (step S209), the moire suppressing unit 106 performs color suppression on the pixel determined to be a part of moire, wherein the pixel color in the moire range can be suppressed to be gray scale, or different suppression magnifications are set according to different degrees, and the color of the pixel is suppressed to be gray scale (step S211), and finally the output result, that is, the output image 107 subjected to moire suppression is output (step S213).

Reference may be made to a schematic diagram of an embodiment of determining a moire direction in the method for determining moire illustrated in fig. 3.

Fig. 3 shows a 5 × 5 pixel array area in the image, and the practical implementation can select the appropriate pixel array according to the hardware resources, and this embodiment uses the Y value (luminance value) of the pixel in the YUV color space as the basis for calculation. The pixel currently determined in the 5 × 5 pixel array is Y (i, j), which is used as the origin of the region to mark the neighboring pixels, for example, the horizontal pixel of the current pixel Y (i, j) includes: y (i, j-2), Y (i, j-1), Y (i, j +1), and Y (i, j + 2); the vertical pixel includes: y (i-2, j), Y (i-1, j), Y (i +1, j), and Y (i +2, j); the major diagonal (top left and bottom right) pixels include: 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 having vertical moire, in a detection window, a central pixel is a current pixel 40, according to the characteristics of the vertical moire, the characteristic of the vertical moire is that the luminance value of the pixel in the vertical direction is relatively close to that of other directions (a threshold may be set to determine the degree of the proximity), and besides the pixel in the vertical direction, the luminance value difference between the current pixel 40 and other adjacent pixels (left, right, upper left, lower left, upper right, and lower right) should be relatively large (a threshold may be set to determine the difference), so that the characteristic can be used to find the vertical moire.

Fig. 4B is a schematic diagram of a pixel array having horizontal moire, and similarly, in fig. 4B, the pixel brightness value of the central pixel is the current pixel 40 ', and in addition to the pixel in the horizontal direction, the brightness value difference between the current pixel 40' and other adjacent pixels (upper, lower, upper left, lower left, upper right, and lower right) is relatively large, so that the current pixel can also be used to search for the horizontal moire.

The first embodiment is as follows: horizontal and vertical moire.

Combining the above horizontal and vertical moire features, as shown in fig. 5A to 5C, the moire can be determined by calculating the difference between the brightness (e.g., Y value) of the current pixel 50 and the brightness (e.g., Y value) of the adjacent diagonal (diagonal) pixel (called the key pixel) to determine whether there is a moire in the horizontal or vertical direction. Fig. 5A uses the central pixel as the current pixel 50 and the luminance difference between the diagonal pixels (indicated by arrows) as the basis for determining horizontal or vertical moire. Fig. 5B is another representation of the requirement for the difference between the brightness values of several key pixels in the 5 × 5 pixel array and their diagonal pixels (as indicated by arrows) as the basis for determining horizontal or vertical moire. Fig. 5C shows an example of a weight mask (mask) set for the key pixels and their neighboring pixels in the detection window, wherein the weight mask is designed according to the type to be determined, and a higher weight value, in this

embodiment

4 and 1, may be given to the key pixels when calculating the moire response value, and when the lower pixel 50 may have the highest weight value of 4, the rest of the key pixels are set as weight values of 1, which are used as coefficients of an algorithm; conversely, the key pixel is given a lower weight value (in this embodiment, -2) to the diagonal neighboring pixels, thereby emphasizing the spatial distribution characteristics of the image.

Referring to the pixels labeled in fig. 3 and fig. 5A to 5C, formula a represents calculating the horizontal or vertical moire response value of the specific area corresponding to the detection window for each pixel in the image by using the detection window, formula a shows that the first half of formula "(" 4 × Y (i, j) + Y (i-2, j) + Y (i, j +2) + Y (i +2, j) + Y (i, j-2)) ") is used to calculate the sum of luminance values of several key pixels in a certain image area, and in particular, the sum may be multiplied by the weight values shown in fig. 5C; the second half of formula a, the expression "(2 x Y (i-1, j-1) +2 x Y (i-1, j +1) +2 x Y (i +1, j-1))" is to calculate the sum of the luminance values of the diagonal neighboring pixels of the key pixel (which can be multiplied by the weight values shown in fig. 5C). The preceding and subsequent expressions of formula a are subtracted and an absolute value is taken to obtain a luminance value gradient (gradient) in the pixel region, when the luminance value gradient of the entire image is calculated, the larger the difference (absolute value) is, the more prominent the horizontal or vertical Moire in the image is, otherwise, the difference indicates that no significant Moire is present, the difference indicates the Moire response value (Moire _ HVEdge) in the horizontal and vertical directions, that is, the edge characteristic of the pixel is obtained to determine whether the Moire feature is present therein, and the phenomenon that Moire is generated when the sampling frequency of the pixel is consistent with or close to the spatial frequency of the Moire is also 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)) | (formula A)

Then, using the detection window to compare the brightness values of the key pixels and the corresponding adjacent pixels in the pixel region one by one, and making statistics to detect the edge and determine the edge as the moire pattern. Formula B and formula C represent statistical horizontal or vertical moire feature comparisons. 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, where KHV represents the difference between the pixel values set by the user, according to the actual ambient light source, it is determined that 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 adjacent key pixels in the horizontal and vertical directions is greater than (the brightness value is at least greater than KHV), which can be determined as the threshold of moire. In this case, the luminance value comparison and statistics may be performed only for pixels identified as part of the moire pattern by the moire response value.

Formula 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 current pixel luminance value Y (i, j) is a relatively low luminance value, as shown in formula C, the difference between the luminance 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 pixels in the horizontal and vertical directions is greater than (the luminance difference threshold is increased by KHV), which can be determined as the moire threshold.

Formula 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)

then, the statistical results of the horizontal and vertical moire features obtained by formula B and formula C are compared, for example, formula D, and the statistical result that the current pixel brightness value Y (i, j) is relatively high and low is compared, so as to determine whether the current pixel is relatively high or low in brightness with respect to the neighboring pixels.

Formula D:

example two: major diagonal moir é.

For the main diagonal type, the features of the diagonal moire are synthesized, as shown in fig. 6A to 6C, the same example is taken as a 5 × 5 pixel array in the figure, as shown in fig. 6A, the central pixel is the current pixel 60, and the method for determining moire determines whether there is a dominant diagonal moire by calculating the difference between the luminance values (e.g., Y values) of the current pixel 60 and the horizontal and vertical neighboring pixels, as shown by the arrow in the figure, the difference between the luminance values of the current pixel 60 and the horizontal and vertical pixels is used as the basis for determining the dominant diagonal moire. Fig. 6B is also another representation, in which the difference between the brightness values of several key pixels in the 5 × 5 pixel array and their horizontal and vertical neighbors (as indicated by arrows) is used as the basis for determining the dominant diagonal moire. Fig. 6C shows an example of a weight mask (mask) showing that when calculating the moire response value, key pixels are given higher weight values, 4 and 1 in this embodiment, when the pixel 60 can be set with the highest weight value of 4, and the rest of key pixels are set to weight values of 1; conversely, the pixels in the horizontal and vertical directions of the key pixel are given lower weight values (in this embodiment, the weight value is-2), so that the spatial distribution characteristic of the image can be emphasized.

Referring to the pixels labeled in fig. 3 and fig. 6A to 6C, formula E is to calculate the main diagonal moire response value of the specific region corresponding to the detection window for each pixel in the image by using the detection window, and similarly, formula E shows the first half of the formula in the absolute value of "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 to calculate the sum of the luminance values of several key pixels in a certain image region, and particularly may be multiplied by the weight values shown in fig. 6C; the second half of equation E, equation "(2 x Y (i-2, j) +2 x Y (i, j +2) +2 x Y (i +2, j) +2 x Y (i, j-2))", is used to calculate the sum of the luminance values of the horizontally and vertically adjacent pixels of the key pixel (e.g., the current pixel Y (i, j)) (which may be multiplied by the weight values shown in fig. 6C). Subtracting the preceding and subsequent expressions of the formula E and taking an absolute value to obtain the brightness value gradient in the pixel region, wherein 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 significant moire is indicated. This difference is the Moire response value (Moire _ DIAG _ POSEdge) in the main diagonal direction, and the edge characteristics of the pixel are obtained to determine whether Moire features are present therein.

Formula 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 the plurality of key pixels and the corresponding adjacent pixels in the pixel region are compared one by one for each pixel by using the detection window, and statistics is performed to detect the edge characteristics and determine the edge characteristics as moire fringes. And the formula F and the formula G represent the comparison value of the statistical main diagonal moire characteristics. 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 a pixel value difference set by the user, according to the actual ambient light source, the threshold value for determining that the brightness value difference between the key pixel (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 adjacent pixel in the main diagonal direction is greater than (the brightness value is at least greater than KD) can be determined as moire. In this case, the luminance value comparison and statistics may be performed only for pixels identified as part of the moire pattern by the moire response value.

Formula 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 current pixel is a relatively low luminance value, as shown in formula G, KD is also used as a threshold for determining that the luminance value difference between the key pixel and its neighboring pixels in the main diagonal direction is greater than (increasing the luminance difference threshold by KD), which can be determined as moire.

Formula 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)

then, the statistical results of the dominant diagonal moire features obtained by the formula F and the formula G are compared, for example, the formula H, and the statistical results of the current pixel brightness value Y (i, j) being relatively high and low are compared, so as to determine that the current pixel is a pixel with relatively high or low brightness.

Formula H:

example three: sub diagonal moir é.

For the sub diagonal type, as shown in fig. 7A to 7C, taking a 5 × 5 pixel array as an example, as shown in fig. 7A, the central pixel is the current pixel 70, and the method for determining moire determines whether there is moire in the sub diagonal direction by calculating the difference between the brightness values (e.g., Y value) of the current pixel 70 and the horizontal and vertical neighboring pixels, as shown by the arrow in the figure. FIG. 7B shows another way of determining the sub-diagonal moire, which is the difference between the luminance values of several key pixels in a 5 × 5 pixel array and their horizontal and vertical neighbors (as indicated by arrows). Fig. 7C shows an example of a proposed weight mask (mask) for determining a sub-diagonal moire, which shows that a higher weight value is given to a key pixel when calculating a moire response value, 4 and 1 in this embodiment, when a pixel 70 may be set with a highest weight value of 4, the rest of key pixels are set as weight values of 1; conversely, the pixels in the horizontal and vertical directions of the key pixel are given lower weight values (in this embodiment, the weight value is-2), so that the spatial distribution characteristic of the image can be emphasized.

Referring to the pixels labeled in fig. 3 and fig. 7A to 7C, formula I is to calculate the sub-diagonal moire response value of the specific region corresponding to the detection window for each pixel in the image by using the detection window, and similarly, formula I shows the first half of the formula in the absolute value of "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 to calculate the sum of the luminance values of several key pixels in a certain image region, and particularly, the sum can be multiplied by the weight value shown in fig. 7C; the second half of formula I, formula "((2 x Y (I-2, j) +2 x Y (I, j +2) +2 x Y (I +2, j) +2 x Y (I, j-2))") is used to calculate the sum of the luminance values of the horizontally and vertically adjacent pixels of the key pixel (e.g., the current pixel Y (I, j)) (which may be multiplied by the weight values shown in fig. 7C). Subtracting the preceding and subsequent formulas of formula I and taking an absolute value to obtain the brightness value gradient in the pixel region, wherein once the brightness value gradient of the whole image is calculated, the larger the difference (absolute value), the more the sub-diagonal moire in the image is highlighted; otherwise, no significant moire is indicated. This difference is the Moire response value (Moire _ DIAG _ POSEdge) in the sub diagonal direction, and the edge characteristics of the pixel are obtained to determine whether Moire features are present therein.

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 the plurality of key pixels and the corresponding adjacent pixels in the pixel region are compared one by one for each pixel by using the detection window, and statistics is performed to detect the edge characteristics and determine the edge characteristics as moire fringes. Formula J and formula K represent the comparison value of the statistical sub-diagonal moire features. 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 J, wherein KD represents a pixel value difference set by the user, and the difference between the brightness values of the key pixel and its neighboring pixels in the sub-diagonal direction is determined to be greater than the threshold value for determining the moire pattern according to the actual ambient light source. In this case, the luminance value comparison and statistics may be performed only for pixels identified as part of the moire pattern 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 current pixel is a relatively low luminance value, as shown in formula K, KD is also used as a threshold for determining that the luminance value difference between the key pixel and its neighboring pixels in the sub-diagonal direction is greater than (the luminance difference threshold is increased by KD), which can be determined as moire.

Formula 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)

then, the statistical results of the sub-diagonal moire features obtained by formula J and formula K are compared, for example, formula L, to compare the statistical results that the current pixel brightness value Y (i, J) is relatively high and low, so as to determine 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 fringes, the horizontal-vertical and positive/negative diagonal moire response values are calculated, then the luminance information of the current pixel and the luminance information of the neighboring pixels in the horizontal-vertical and positive/negative diagonal directions are compared, and the comparison result is counted, so as to determine the luminance characteristic of the current pixel compared with the neighboring pixels. The method includes determining whether a current pixel is a moire pattern according to a threshold set by a system and a moire pattern response value and a statistical result, including determining a position and a type of a moire pattern in an image.

According to one embodiment, when the moire response value is larger than the first threshold, it can be determined that the current pixel has a definite brightness change from its neighboring pixels, and thus can be determined as an edge pixel of the image, i.e. 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, it cannot be determined that the current pixel has the characteristics of moire. When the moire feature comparison value is larger than the second threshold, the characteristic that the current pixel is relatively bright or relatively dark is judged, and the current pixel can be determined to be a part of the moire by matching the judgment that the moire response value is larger than the first threshold.

When the moire in the image is determined, the circuitry may perform color noise reduction on the pixel determined to be moire, for example, color suppression on the pixel determined to be moire in the YUV color space, such as the UV (chroma-density) plane when Y is 128 in the YUV color space as shown in fig. 8. And mapping the pixels judged as the Moire patterns in a chrominance-concentration plane in the YUV color space, wherein 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 respectively representing different colors according to different quadrants.

According to the color U/V value of the moir é pixel located at the coordinate position of the color space, the chromaticity-density plane can be divided into two or three regions to perform different color processing, as shown in fig. 8, the central region represents a color suppression range 801, the pixel colors falling within the color suppression range 801 are all suppressed to gray scale, and then the image with the color moir é suppressed is output.

According to one embodiment, the color-density plane may have three regions, wherein a region enclosed by a dotted line to the color suppression progressive range 801 represents a color suppression progressive range 803, and the pixel colors within the color suppression progressive range 803 between the color suppression range 801 and the dotted line are adjusted and set with a suppression magnification according to the distance from the coordinate center 80, so as to perform color suppression according to the suppression magnification, such as applying different gray scale levels. The suppression ratio can be changed linearly or nonlinearly, and the colors outside the dotted 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 it is still necessary to ensure coverage of the coordinate center 80, and the rectangular area can be flexibly moved to cover the color to be suppressed in different applications or according to the user's preference. The color suppression formula is as formula M:

cout ═ Cin-128 (1-supp _ rate) +128 (formula M)

Wherein Cin is the input U or V value, Cout is the corresponding output U or V value, and supp _ rate is the suppression ratio between 0 and 1. The suppression ratio is calculated by the distance from the coordinate center 80 in the color suppression progressive range 803, the suppression ratio is gradually decreased as the distance from the center is farther, the calculation method of the suppression ratio from 0 to 1 can be obtained by Interpolation (Interpolation), filtering (Filter) and other methods, the value 128 in the formula M is the required displacement 128 when the U and V values in the YUV color space range from 0 to 255 in this example, and the conversion to the coordinate plane is performed, the actual implementation can be modified according to the actual requirements, and the calculation of the suppression ratio is not limited to the illustrated method.

According to the above embodiments, the flow of the moire judgment method and the moire inhibition method operating in the circuit system first obtains the luminance information of each pixel in a color space in the received image, can select a detection range, obtains the spatial distribution characteristics according to the luminance relationship between the pixels, obtains the edge characteristics of the pixels, further judges whether the moire exists and whether the moire is of a horizontal, vertical or positive/negative diagonal type, then performs statistics on the feature comparison values of the moire of a specific type, can determine whether the pixel is a moire part, and then performs color moire inhibition on the pixel determined as 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 the image, the circuit system makes a judgment on moire processing of the pixels one by one, and obtains the relationship between the current pixel and its neighboring pixel values (such as luminance values in particular) according to a detection window to obtain the characteristics of the image spatial distribution. According to the above embodiment, when the moire in the horizontal or vertical direction is set, the key pixel in the detection window is selected, the weighting value is assigned, and the horizontal and vertical moire response values are calculated, that is, the luminance difference between the key pixel and the adjacent pixel is compared with the first threshold value and then used as the basis for determining the moire direction.

In step S903, after processing each pixel one by one, determining whether the image has moire fringes in the horizontal or vertical direction, if the image has horizontal or vertical moire, performing color suppression on the pixel where the moire position is determined (step S907), and outputting the image (step S909); otherwise, the flow continues to step S905, where it is determined whether there are moire fringes in the positive or negative diagonal direction in the image, and similarly, if it is determined that there are moire fringes in the diagonal direction in the image, in step S907, color suppression is performed on the positions of the moire fringes, and the image is output after completion (step S909); on the other hand, if the moire pattern in the diagonal direction is not obtained in the image, indicating that no clear moire pattern is found in the image, the image is directly output (step S909). Thus, the method and the circuit system for judging and suppressing moire disclosed by the specification are realized.

The disclosure is only a preferred embodiment of the invention and should not be taken as limiting the scope of the invention, so that the invention is not limited by the disclosure of the invention.

[ notation ] to show

Original image 101

Color space conversion unit 102

Moire response value calculation unit 103

Moire pattern feature statistics unit 104

Moire pattern determination unit 105

Moire pattern suppression unit 106

Output image 107

The

lower pixel

40, 40', 50,60,70

Coordinate center 80

Color suppression Range 801

Color suppressed progressive range 803

Method flow for judging and inhibiting Moire patterns in steps S201-S213

Method flow for judging and inhibiting Moire patterns in steps S901-S909

Claims

1. A method of determining moir é, comprising:

acquiring brightness information of a plurality of pixels in an image;

a detection window is arranged, and a plurality of key pixels for judging the moire type are selected from the detection window;

calculating a moire response value of the plurality of key pixels and a plurality of corresponding adjacent pixels through the detection window aiming at each pixel, wherein the moire response value is used for judging whether the image has moire features;

aiming at each pixel, comparing the brightness information of the key pixels and the corresponding adjacent pixels by using the detection window, and counting the comparison result to judge the brightness characteristic of each pixel; and

and confirming the position and the type of the moire in the image according to the moire response value and the statistical result.

2. The method of 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 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 the image into the luma-chroma-density color space or the red-green-blue color space when the image is obtained.

4. The method according to claim 1, wherein in the step of calculating the moire response value, a weight mask is set in the detection window, and the moire response value is calculated by multiplying the plurality of key pixels and the corresponding plurality of neighboring pixels by weight values respectively.

5. The method according to claim 4, wherein in the step of calculating the moire response value, the weight mask is designed according to the type of moire to be determined, the plurality of key pixels are given higher weight values, and the plurality of neighboring pixels are given lower weight values.

6. The method according to claim 5, wherein the moire response value calculated for each pixel is compared with a first threshold to obtain the brightness variation of the pixel and its neighboring pixels, and further determining whether the image has moire features.

7. The method of claim 1, wherein a second threshold is introduced to determine the brightness characteristic of each pixel when comparing the brightness information of the key pixels with the brightness information of the corresponding neighboring pixels.

8. The method according to any one of claims 1 to 7, wherein the moire is of a type of moire in horizontal and vertical directions, a type of moire in a major diagonal direction, or a type of moire in a minor diagonal direction.

9. A method of suppressing moir é, comprising:

obtaining an image, converting the image into a luminance-chrominance-density color space, and obtaining luminance values of a plurality of pixels in the image;

calculating a moire response value of the plurality of key pixels and a plurality of corresponding adjacent pixels aiming at each pixel passing through the detection window, wherein the moire response value is used for judging whether the image has moire features;

aiming at each pixel, comparing the brightness values of the key pixels and the corresponding adjacent pixels by using the detection window, and counting the comparison result to judge the brightness characteristic of each pixel;

confirming the position and the type of the moire in the image according to the moire response value and the statistical result;

and carrying out color noise reduction on a plurality of pixels judged as Moire patterns, wherein:

mapping a plurality of pixels judged to be Moire patterns on a chroma-chroma plane of the luma-chroma color space; and

and suppressing the pixel colors in a color suppression range in the chromaticity-concentration plane into gray scales.

10. A circuit system, comprising:

a processor and a memory, wherein the processor executes a Moire pattern determining method, comprising:

aiming at each pixel, comparing the brightness values of the key pixels and the corresponding adjacent pixels by using the detection window, and counting the comparison result to judge the brightness characteristic of each pixel; and

and confirming the position and the type of the moire pattern in the image according to the moire pattern response value and the statistical result so as to carry out color noise reduction on a plurality of pixels judged to be moire patterns.