Image processing method, device and storage medium

Abstract

The present disclosure provides an image processing method, device and storage medium, the method comprising: extracting a red, green and blue channel image and a white channel image from a target image; determining a first gray component image of the red, green and blue channel image, and determining a second gray component image of the white channel image; determining first decomposition subband information of the first gray component image, and determining second decomposition subband information of the second gray component image; determining third decomposition subband information according to the first decomposition subband information and the second decomposition subband information; reconstructing an image according to the third decomposition subband information to obtain a third gray component image, and constructing a color image corresponding to the target image according to the third gray component image. In the present disclosure, the information of the W channel image is used to compensate the RGB channel image, improve the signal-to-noise ratio of the image under low illumination, improve the overall brightness of the image, and improve the image quality.

Description

Technical Field

[0001] The present disclosure relates to the technical field of mobile terminal data processing, and in particular to an image processing method, device and storage medium. Background Art

[0002] With the continuous development of camera technology, traditional types of imaging sensors can no longer meet the new requirements in imaging. A variety of new imaging sensors have gradually emerged, which can effectively combine the advantages of images collected by different channels of image sensors to improve the output image quality.

[0003] At present, the common sensors used in mobile terminals are arranged in RGGB arrays. Since the R, G, and B channels of the traditional RGGB array sensors can only pass spectral energy in a narrow band, the sensor can collect less energy. When taking images under low illumination, the image brightness is low and the signal-to-noise ratio is low. Summary of the invention

[0004] To overcome the problems existing in the related art, the present disclosure provides an image processing method, device and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, there is provided an image processing method, including:

[0006] Extract red, green, blue channel images and white channel image from the target image;

[0007] Determine a first grayscale component image of the red, green and blue channel images, and determine a second grayscale component image of the white channel image;

[0008] Determine first decomposition subband information of the first gray component image, and determine second decomposition subband information of the second gray component image; the first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix;

[0009] Determine third decomposition subband information according to the first decomposition subband information and the second decomposition subband information;

[0010] An image is reconstructed according to the third decomposition sub-band information to obtain a third gray component image, and a color image corresponding to the target image is constructed according to the third gray component image.

[0011] In one embodiment, the determining the first decomposition subband information of the first gray component image and the determining the second decomposition subband information of the second gray component image include:

[0012] Using an image multi-scale decomposition method, determining first decomposition sub-band information of the first gray component image and determining second decomposition sub-band information of the second gray component image;

[0013] The number of decomposition layers in the first decomposition sub-band information and the number of frequency bands in each decomposition layer are the same.

[0014] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0015] The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer;

[0016] For each frequency band under each decomposition layer in the third decomposition subband information, the frequency band coefficient matrix of the corresponding frequency band in the third decomposition subband information is calculated according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0017] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0018] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0019] For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0020] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0021] Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0022] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

[0023] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0024] Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0025] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0026] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0027] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0028] For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0029] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0030] In one embodiment, determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information includes:

[0031] Determining a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; and the eighth matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the second decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the second decomposition sub-band information;

[0032] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band;

[0033] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band;

[0034] Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

[0035] According to a second aspect of an embodiment of the present disclosure, there is provided an image processing apparatus, including:

[0036] An extraction module is configured to extract a red, green, blue channel image and a white channel image from a target image;

[0037] A first determination module is configured to determine a first gray component image of the red, green and blue channel images, and to determine a second gray component image of the white channel image;

[0038] The second determination module is configured to determine first decomposition subband information of the first gray component image, and to determine second decomposition subband information of the second gray component image; the first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix;

[0039] A third determining module is configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information;

[0040] The construction module is configured to reconstruct an image according to the third decomposition sub-band information to obtain a third gray component image, and construct a color image corresponding to the target image according to the third gray component image.

[0041] In one embodiment, the second determination module is further configured to determine the first decomposition sub-band information of the first gray component image and determine the second decomposition sub-band information of the second gray component image using the following method:

[0042] Using an image multi-scale decomposition method, determining first decomposition sub-band information of the first gray component image and determining second decomposition sub-band information of the second gray component image;

[0043] The number of decomposition layers in the first decomposition sub-band information and the number of frequency bands in each decomposition layer are the same.

[0044] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0045] The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer;

[0046] For each frequency band under each decomposition layer in the third decomposition subband information, the frequency band coefficient matrix of the corresponding frequency band in the third decomposition subband information is calculated according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0047] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0048] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0049] For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0050] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0051] Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0052] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

[0053] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0054] Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0055] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0056] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0057] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0058] For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0059] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0060] In one embodiment, the third determination module is further configured to determine the third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0061] Determining a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; and the eighth matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the second decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the second decomposition sub-band information;

[0062] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band;

[0063] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band;

[0064] Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

[0065] According to a third aspect of an embodiment of the present disclosure, there is provided an image processing apparatus, including:

[0066] processor;

[0067] a memory for storing processor-executable instructions;

[0068] Wherein, the processor is configured to execute the above method.

[0069] According to a fourth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided, which enables the mobile terminal to execute the above method when instructions in the storage medium are executed by a processor of the mobile terminal.

[0070] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: extracting a first gray component image of an RGB channel image and a second gray component image of a W channel image from a target image, fusing the decomposed subband information of the two gray component images, using the information of the W channel image to compensate for the RGB channel image, improving the signal-to-noise ratio of the image under low illumination, improving the overall brightness of the image, and improving the image quality.

[0071] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0073] Figure 1 is a flowchart of an image processing method according to an exemplary embodiment;

[0074] Figure 2 is a schematic diagram showing image extraction of an RGBW channel image according to an exemplary embodiment;

[0075] Figure 3 is a structural diagram of an image processing device according to an exemplary embodiment;

[0076] Figure 4 is a structural diagram of an image processing device according to an exemplary embodiment. DETAILED DESCRIPTION

[0077] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0078] The present disclosure provides an image processing method. Figure 1 , Figure 1 FIG. 1 is a flowchart of an image processing method according to an exemplary embodiment. Figure 1 As shown, this method includes:

[0079] Step S11, extracting red, green, blue channel images and a white channel image from the target image.

[0080] Step S12, determining the first gray component images of the red, green and blue channel images and determining the second gray component image of the white channel image.

[0081] Step S13, determine the first decomposition subband information of the first grayscale component image, and determine the second decomposition subband information of the second grayscale component image; the first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix.

[0082] Step S14: determining third decomposition subband information according to the first decomposition subband information and the second decomposition subband information.

[0083] Step S15, reconstructing the image according to the third decomposition sub-band information to obtain a third gray component image, and constructing a color image corresponding to the target image according to the third gray component image.

[0084] In this embodiment, a first gray component image of the RGB channel image and a second gray component image of the W channel image are extracted from the target image, the decomposed subband information of the two gray component images are fused, and the RGB channel image is compensated using the information of the W channel image, which can improve the signal-to-noise ratio of the image under low illumination, improve the overall brightness of the image, and improve the image quality.

[0085] In one embodiment, the target image in step S11 may be an original RAW format image acquired by an image sensor having red (R) primary color pixels, green (G) primary color pixels, blue (B) primary color pixels, and white (W) pixels, and the original RAW format image acquired by this image sensor may include an RGB channel image and a W channel image. For example, this image sensor may be an image sensor having an RGBW array arrangement, and the image sensor may acquire an RGBW channel image, wherein the RGBW channel image refers to an image in which each pixel is composed of a red (R) primary color pixel, a green (G) primary color pixel, a blue (B) primary color pixel, and a white (W) pixel. Compared with a sensor arranged based on an RGGB array, a sensor arranged based on an RGBW array replaces part of the G channel with a W (white) channel.

[0086] When the target image is an RGBW channel image, the RGB channel image (i.e., the red, green, and blue channel image) and the W channel image (i.e., the white channel image) can be extracted from the RGBW channel image in step S11; for example, the RGB channel image can be, for example, a Bayer RGB format image, and the RGBW channel image data arranged in the RGBW array can be split into two data, namely, a Bayer RGB format image and a W channel image in step S11. When splitting the RGBW channel image into a Bayer RGB format image and a W channel image, the pixel values ​​of the same type at the diagonal position can be binned, that is, the operation of adding and then dividing by two can be adopted. Figure 2 As shown in the figure, the input RGBW channel image of size 4*4 is split into a Bayer RGB format image and a white channel image of size 2*2. The Bayer RGB format image and the white channel image are processed by their respective image processing pipelines (ISP pipeline) and the processed YUV images are output respectively. The Y channel images are extracted from the two YUV images respectively to obtain the corresponding gray component images. In subsequent processing, image fusion processing can be performed based on the gray component images.

[0087] The RGB channel image includes R component, G component and B component. There are many ways to construct RGB channel images, such as Figure 2 Each 2*2 RGGB format RGB channel image shown includes 1 R component, 1 B component and 2 G components. In RGB channel images of other formats, it can include 1 R component, 2 B components and 1 G component, or include 2 R components, 1 B component and 1 G component. And the layout of the components is the same as Figure 2 The layout shown is different.

[0088] In step S12, the decomposed subband information of the gray component image can be determined using an image multiscale decomposition method. The image multiscale decomposition method is used to decompose the original image into multiple images of different scales, and the decomposed different decomposed images express image information of different frequency bands. For example, in step S12, the first decomposition subband information of the first gray component image is determined using a first image multiscale decomposition method; and the second decomposition subband information of the second gray component image is determined using a second image multiscale decomposition method. The first image multiscale decomposition method and the second image multiscale decomposition method may be the same or different.

[0089] In step S15, constructing a color image corresponding to the target image according to the third gray component image may include: using the third gray component image and the chroma component image and the color saturation component image in the YUV image corresponding to the RGB channel image to construct a new YUV image, or using the third gray component image and the chroma component image and the color saturation component image in the YUV image corresponding to the RGB channel image to construct a new YUV image, and converting the YUV image into an RGB image.

[0090] In this embodiment, an original RAW format image can be acquired from an image sensor with an RGBW array arrangement, an RGB channel image and a W channel image can be extracted from the original RAW format image, a first decomposition subband information of a first grayscale component image of the RGB channel image is determined, a second decomposition subband information of a second grayscale component image of the W channel image is determined, the two decomposition subband information are fused, and the RGB channel image is compensated using the information of the W channel image, thereby improving the signal-to-noise ratio of the image under low illumination, improving the overall brightness of the image, and improving the image quality.

[0091] When the present embodiment is used to process the RGBW channel image, the signal-to-noise ratio of the fused image (e.g., the fused RGB image) can be effectively improved, the overall brightness of the image can be improved, and the image quality can be improved. The specific analysis is as follows: Compared with the traditional RGGB structure image sensor, the W channel of the RGBW structure image sensor can pass the energy of the full-color spectrum, so under the same exposure time, the W channel can obtain higher brightness. The conventional fusion method for the RGB channel and the W channel of the RGBW image sensor is as follows: the image collected by the sensor arranged in the RGBW array is split into an RGB channel image and a W channel image, and the RGB channel image and the W channel image are processed through the image processing pipeline (ISP pipeline) respectively, and the processed YUV format image is output, and the weight of the Y channel image in the YUV image corresponding to the RGB channel image is assigned to be 0.5, and the weight of the Y channel image in the YUV image corresponding to the W channel image is also assigned to be 0.5, and the two Y channel images are image fused, and the chroma component image and the color saturation component image in the YUV image corresponding to the RGB channel image are constructed into a new RGB image, thereby achieving the purpose of fusing the RGB channel information with the W channel information. This method of directly using the same weight for the Y channel image corresponding to the RGB channel image and the Y channel image corresponding to the W channel image will cause a significant decrease in image contrast and loss of image details, which has a greater impact on image quality. Therefore, after using the method in this embodiment to process the RGBW image, the signal-to-noise ratio of the fused image (such as the fused RGB image) can be effectively improved, the overall brightness of the image can be increased, and the image quality can be improved.

[0092] The present disclosure provides an image processing method, which includes: Figure 1 The method shown, and the multi-scale image processing algorithm can be a multi-scale image processing algorithm based on wavelet transform, or can be a multi-scale image processing algorithm based on Laplacian pyramid.

[0093] The image multi-scale processing algorithm includes the image multi-scale decomposition algorithm and the image multi-scale reconstruction algorithm. The image multi-scale reconstruction algorithm is the inverse algorithm of the image multi-scale decomposition algorithm.

[0094] Different wavelet bases can be used in the multi-scale image processing algorithm of wavelet transform. For example, the available wavelet bases may include one of the following: Haar, Daubechies, Biorthogonal, Coiflets, Symlets, Morlet, Mexican.

[0095] In the multi-scale image decomposition algorithm of wavelet transform, at the first decomposition layer, the image is decomposed into a low-frequency band sub-image and three high-frequency band sub-images, and a low-frequency band wavelet coefficient matrix and three high-frequency band wavelet coefficient matrices are obtained. In the subsequent decomposition layers, the low-frequency band image in the previous decomposition layer is further decomposed into a low-frequency band sub-image and three high-frequency band sub-images, and so on.

[0096] The method of calculating the multi-scale coefficients of an image using a multi-scale image decomposition algorithm based on wavelet transform may include:

[0097] The image is decomposed into a low-frequency band sub-image and three high-frequency band sub-images, and a low-frequency band wavelet coefficient matrix and three high-frequency band wavelet coefficient matrices are obtained. The low-frequency band wavelet coefficient matrix corresponds to the LL band, which is a band containing low-frequency information of the image. The three high-frequency band wavelet coefficient matrices correspond to the HH band, LH band and HL band respectively. Among them, the HH band is a band containing diagonal high-frequency information of the image, the LH band is a band containing horizontal high-frequency information of the image, and the HL band is a band containing vertical high-frequency information of the image.

[0098] Thus, in the first decomposition layer, a low-frequency wavelet coefficient matrix is ​​included, including the coefficients of each pixel on the low-frequency image, using X LL，1 (i, j) represents the coefficient of the pixel (i, j) in the decomposed image corresponding to the LL band of the first decomposition layer, i represents the row position of the current pixel in the corresponding image, and j represents the column position of the current pixel in the corresponding image.

[0099] The first decomposition layer also includes three high-frequency wavelet coefficient matrices, namely X HH，1 (i,j),X LH，1 (i,j),X HL，1(i,j).

[0100] Among them, X HH，1 (i, j) represents the coefficient of the pixel (i, j) in the decomposed image corresponding to the HH frequency band of the first decomposition layer; X LH，1 (i, j) represents the coefficient of the pixel (i, j) in the decomposed image corresponding to the LH band of the first decomposition layer; X HL，1 (i, j) represents the coefficient of the pixel (i, j) in the decomposed image corresponding to the HL band of the first decomposition layer. The coefficients of each band of other decomposition layers are expressed in the same way.

[0101] In the second decomposition layer, the low-frequency band wavelet image obtained in the first decomposition layer is further decomposed into a low-frequency band sub-image and three high-frequency band sub-images to obtain a low-frequency band wavelet coefficient matrix and three high-frequency band wavelet coefficient matrices.

[0102] Thus, in the second decomposition layer, a low-frequency band wavelet coefficient matrix is ​​included, labeled X LL,2 (i, j), and the three high-frequency band wavelet coefficient matrices are X HH,2 (i,j),X LH,2 (i,j),X HL,2 (i,j).

[0103] In the third decomposition layer, the low-frequency band wavelet image obtained in the second decomposition layer is further decomposed into a low-frequency band sub-image and three high-frequency band sub-images, obtaining a low-frequency band wavelet coefficient matrix and three high-frequency band wavelet coefficient matrices.

[0104] Thus, in the third decomposition layer, there is a low-frequency band wavelet coefficient matrix, labeled X LL,3 (i, j), and the three high-frequency band wavelet coefficient matrices are X HH,3 (i,j),X LH,3 (i,j),X HL,3 (i,j).

[0105] And so on.

[0106] The principle of the image pyramid method is to decompose the original image into a multi-scale pyramid image sequence, with low-resolution images in the upper layer and high-resolution images in the lower layer. The size of the upper layer image is 1 / 4 of the size of the previous layer image. The pyramids of all images are fused at the corresponding layer according to certain rules to obtain a synthetic pyramid, which is then reconstructed according to the inverse process of pyramid generation to obtain a fused pyramid.

[0107] The present disclosure provides an image processing method, which includes: Figure 1The method shown in FIG. 1 , and determining the first decomposition subband information of the first gray component image in step S12, and determining the second decomposition subband information of the second gray component image may include:

[0108] An image multi-scale decomposition method is adopted to determine the first decomposition subband information of the first gray component image and the second decomposition subband information of the second gray component image; the number of decomposition layers in the first decomposition subband information and the second decomposition subband information is the same, and the number of frequency bands in each decomposition layer is the same.

[0109] For example, using the image multi-scale decomposition method of wavelet transform based on Haar wavelet basis, the first gray component image is decomposed into three layers to obtain three decomposition layers, each of which corresponds to frequency band coefficients of four frequency bands.

[0110] In one example, using a multiscale image processing algorithm based on wavelet transform to calculate multiscale decomposition subband information of a Y channel image corresponding to a Bayer RGB format image includes: Because the first decomposition layer is decomposed into four coefficients in the second decomposition layer, so the multi-scale decomposition sub-band information of the RGB channel image does not include Similarly, because the second decomposition layer is decomposed into four coefficients in the third decomposition layer, so the multi-scale decomposition sub-band information of the RGB channel image does not include

[0111] in, Represents the coefficient of the pixel (i, j) in the decomposed image of the RGB channel image corresponding to the HH frequency band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the RGB channel image corresponding to the LH frequency band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the RGB channel image corresponding to the HL band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the LL band of the first decomposition layer corresponding to the RGB channel image. The coefficients of each band of other decomposition layers are expressed in the same way.

[0112] The multi-scale decomposition sub-band information of the Y channel image corresponding to the W channel image is calculated using a multi-scale image decomposition algorithm based on wavelet transform, including:

[0113] Represents the coefficient of the pixel (i, j) in the decomposed image of the W channel image corresponding to the HH frequency band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the W channel image corresponding to the LH frequency band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the W channel image corresponding to the HL band of the first decomposition layer. Represents the coefficient of the pixel (i, j) in the decomposed image of the W channel image corresponding to the LL band of the first decomposition layer. The coefficients of each band of other decomposition layers are expressed in the same way.

[0114] In another embodiment, different image multi-scale decomposition methods are used to determine the first decomposition subband information of the first gray component image and the second decomposition subband information of the second gray component image. For example, the first decomposition method is used to determine the first decomposition subband information of the first gray component image, and the second decomposition method is used to determine the second decomposition subband information of the second gray component image. Both the first decomposition method and the second decomposition method are based on the wavelet transform of the same wavelet basis, but the number of decomposition layers of the first decomposition method is different from the number of decomposition layers of the second decomposition method.

[0115] The present disclosure provides an image processing method, which includes: Figure 1 The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0116] Step S141: The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer.

[0117] Step S142, for each frequency band under each decomposition layer in the third decomposition sub-band information, calculate the frequency band coefficient matrix of the corresponding frequency band in the third decomposition sub-band information according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition sub-band information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition sub-band information.

[0118] In one embodiment, before step S141, the following may also be included: step S140, determining the first decomposition layer number corresponding to the first decomposition sub-band information and the number of frequency bands corresponding to each decomposition layer; determining the second decomposition layer number corresponding to the second decomposition sub-band information and the number of frequency bands corresponding to each decomposition layer.

[0119] When the number of decomposition layers in the first decomposition subband information and the second decomposition subband information is different, or when the number of decomposition layers is the same but the number of corresponding frequency bands in at least one decomposition layer is the same, the same frequency bands of the first decomposition subband information and the second decomposition subband information at the same decomposition layer can be determined in step S141.

[0120] For example, in one example:

[0121] In step S140, the first decomposition layer number corresponding to the first decomposition subband information is 3, and each decomposition layer corresponds to 4 frequency bands. The frequency bands corresponding to the first decomposition layer are LL frequency band, LH frequency band, HL frequency band and HH frequency band under the first decomposition layer; the four frequency bands corresponding to the second decomposition layer are LL frequency band, LH frequency band, HL frequency band and HH frequency band under the second decomposition; the four frequency bands corresponding to the third decomposition layer are LL frequency band, LH frequency band, HL frequency band and HH frequency band under the third decomposition layer.

[0122] The second decomposition layer number corresponding to the second decomposition subband information is 2, and each decomposition layer corresponds to 4 frequency bands. The frequency bands corresponding to the first decomposition layer are the LL frequency band, LH frequency band, HL frequency band and HH frequency band under the first decomposition layer; the four frequency bands corresponding to the second decomposition layer are the LL frequency band, LH frequency band, HL frequency band and HH frequency band under the second decomposition.

[0123] In this example, in step S141, it is determined that the same frequency bands of the first decomposition subband information and the second decomposition subband information at the same decomposition layer may include: four frequency bands at the first decomposition layer and four frequency bands at the second decomposition layer. Thus, it is determined that the third decomposition subband information includes two decomposition layers, and each decomposition layer includes four frequency bands.

[0124] In one embodiment, when the number of decomposition layers in the first decomposition subband information and the second decomposition subband information is the same and the number of frequency bands corresponding to each decomposition layer number is also the same, it is determined that the number of decomposition layers in the third decomposition subband information is the number of decomposition layers of the first decomposition subband information or the second decomposition subband information, and it is determined that the number of frequency bands corresponding to each decomposition layer in the third decomposition subband information is the number of frequency bands in the corresponding decomposition layer in the first decomposition subband information or the second decomposition subband information.

[0125] In step S142, when calculating the frequency band coefficient matrix of a frequency band in the third decomposition sub-band information, the frequency band coefficient matrix corresponding to the same frequency band in the first decomposition sub-band information and the second decomposition sub-band information can be used for calculation. For example:

[0126] The band coefficient matrix of the HH band of the first decomposition layer in the first decomposition subband information is calculated using the band coefficient matrix of the HH band of the first decomposition layer in the first decomposition subband information and the band coefficient matrix of the HH band of the first decomposition layer in the second decomposition subband information.

[0127] The band coefficient matrix of the LL band of the second decomposition layer in the third decomposition subband information is calculated using the band coefficient matrix of the LL band of the second decomposition layer in the first decomposition subband information and the band coefficient matrix of the LL band of the second decomposition layer in the second decomposition subband information.

[0128] The present disclosure provides an image processing method, which includes: Figure 1The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0129] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0130] For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0131] In this embodiment, in different situations, one or more different frequency bands in the third decomposition sub-band information may be set as the set high frequency band.

[0132] In one embodiment, the first decomposition subband information and the second decomposition subband information are decomposition subband information obtained by a multi-scale image decomposition method based on wavelet transform. The high frequency band is set to be the HH frequency band in the first decomposition layer.

[0133] For the set high frequency band, the frequency band coefficient matrix of the set high frequency band corresponding to the second decomposition sub-band information of the W channel image is used as the frequency band coefficient matrix of the set high frequency band of the third decomposition sub-band information. That is, for the HH band in the first decomposition layer:

[0134]

[0135] in, The band coefficients at the pixel (i, j) in the decomposed image corresponding to the HH band of the first decomposition layer in the third decomposition sub-band information are represented. The band coefficients corresponding to other decomposition layers and other bands in the third decomposition sub-band information are the same.

[0136] For each frequency band except the set high frequency band in the third decomposition subband information, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0137] In one example, for the LH band in the first decomposition layer:

[0138]

[0139] For the HL band in the first decomposition layer:

[0140]

[0141] For the HH band in the second decomposition layer, that is, the HH band under the LL band in the first decomposition layer:

[0142]

[0143] For the LH band in the second decomposition layer, that is, the LH band below the LL band in the first decomposition layer:

[0144]

[0145] For the HL band in the second decomposition layer, that is, the HL band below the LL band in the first decomposition layer:

[0146]

[0147] For the HH band in the third decomposition layer, that is, the HH band under the LL band in the second decomposition layer:

[0148]

[0149] For the LH band in the third decomposition layer, that is, the LH band below the LL band in the second decomposition layer:

[0150]

[0151] For the HL band in the third decomposition layer, that is, the HL band below the LL band in the second decomposition layer:

[0152]

[0153] For the LL band in the third decomposition layer, that is, the LL band below the LL band in the second decomposition layer:

[0154]

[0155] in, The coefficient representing the pixel point (i, j) in the decomposed image of the HH frequency band of the third decomposition layer corresponds to the third decomposition sub-band information. The coefficient representing the pixel point (i, j) in the decomposed image of the LH frequency band of the third decomposition layer corresponding to the third decomposition sub-band information. The coefficient representing the pixel point (i, j) in the decomposed image of the HL frequency band of the third decomposition layer corresponding to the third decomposition sub-band information. The coefficient representing the pixel (i, j) in the decomposed image of the LL band of the third decomposition layer corresponding to the third decomposition sub-band information.

[0156] In one embodiment, the frequency band corresponding to the set high frequency band includes the HH frequency band, the LH frequency band and the HL frequency band in the first decomposition layer.

[0157] For the set high frequency band, the band coefficient matrix of the set high frequency band corresponding to the first decomposition subband of the W channel image is used as the band coefficient matrix of the set high frequency band of the third decomposition subband. That is, for the HH band, LH band and HL band in the first decomposition layer:

[0158]

[0159]

[0160]

[0161] For each frequency band except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition sub-band information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition sub-band information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition sub-band information.

[0162] The present disclosure provides an image processing method, which includes: Figure 1 The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0163] Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0164] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

[0165] For example:

[0166] When the number of decomposition layers of wavelet transform is 3, the high frequency band is set to be the HH frequency band in the first decomposition layer. The weighting coefficient corresponding to the second decomposition subband information of the W channel image in the set high frequency band is 0.98, and the corresponding weighting coefficients in the frequency bands other than the high frequency band are all 0.5, 0.6, or 0.55, etc.

[0167] In one example, the high frequency band is set to be the HH frequency band in the first decomposition layer.

[0168] HH band in the first decomposition layer:

[0169]

[0170] For the LH band in the first decomposition layer:

[0171]

[0172] For the HL band in the first decomposition layer:

[0173]

[0174] And so on.

[0175] The present disclosure provides an image processing method, which includes: Figure 1 The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0176] Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0177] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0178] For example, when the number of decomposition layers of the wavelet transform is 3, the weight coefficient corresponding to the second decomposition sub-band information on the frequency band is negatively correlated with the number of the decomposition layer to which the frequency band belongs.

[0179] For example, the weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the first decomposition layer are all greater than the weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the second decomposition layer.

[0180] The weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the second decomposition layer are all greater than the weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the third decomposition layer.

[0181] The present disclosure provides an image processing method, which includes: Figure 1The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0182] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient of the set high frequency band in the third decomposition sub-band information;

[0183] For each frequency band except the set high frequency band in the third decomposition sub-band information, the following operations are performed:

[0184] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0185] For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0186] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0187] For example:

[0188] When the number of decomposition layers of the wavelet transform is 3, the high frequency band is determined to be the HH band in the first decomposition layer. The band coefficient of the HH band in the first decomposition layer in the second decomposition subband information of the W channel image is used as the band coefficient of the HH band in the first decomposition layer in the third decomposition subband information.

[0189] The weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the first decomposition layer are all greater than the weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the second decomposition layer.

[0190] The weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the second decomposition layer are all greater than the weighting coefficients corresponding to the HH band, LH band, HL band and HH band in the third decomposition layer.

[0191] The present disclosure provides an image processing method, which includes: Figure 1The method shown in FIG. 1 , and determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information in step S14 may include:

[0192] Determining a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; and the eighth matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the second decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the second decomposition sub-band information;

[0193] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band;

[0194] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band;

[0195] Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

[0196] The first variance and the second variance corresponding to a pixel are both variance values ​​of pixel values ​​within an area of ​​a set size (eg, a 3x3 area, or a 5x5 area, or a 7x7 area) centered on each pixel.

[0197] In one embodiment, the ratio of the first variance to the second variance corresponding to each pixel point is equal to the ratio of the weighting coefficient corresponding to the pixel point in the decomposition image of the first gray component image on this frequency band and the weighting coefficient corresponding to the pixel point in the decomposition image of the second gray component image on this frequency band.

[0198] For example: HH band in the first decomposition layer:

[0199]

[0200] in, It refers to the weighting coefficient of the second gray component image corresponding to the (i, j) pixel in the decomposed image of this frequency band in the HH frequency band of the first decomposition layer.

[0201] It refers to the weighting coefficient corresponding to the pixel (i, j) of the second gray component image in the decomposed image of this frequency band in the HH frequency band of the first decomposition layer.

[0202] It refers to the second variance of the second gray component image at the pixel (i, j) in the decomposed image of the HH band in the first decomposition layer.

[0203] It refers to the first variance of the first gray component image at the (i, j) pixel in the decomposed image of the HH band in the first decomposition layer.

[0204] For example, when the number of decomposition layers of the wavelet transform is 2, the calculation of the first decomposition subband information of the first gray component image using the multi-scale image decomposition algorithm based on the wavelet transform includes:

[0205] When the number of decomposition layers of the wavelet transform is 2, calculating the second decomposition subband information of the second gray component image using the multi-scale image decomposition algorithm based on the wavelet transform includes:

[0206] For a pixel point in a frequency band, the weighting coefficient corresponding to the pixel point in the decomposition image of the first gray component image in this frequency band and the weighting coefficient corresponding to the pixel point in the decomposition image of the second gray component image in this frequency band are determined according to the first variance and the second variance corresponding to the pixel point. For example, the calculation method for the HH frequency band in the first decomposition layer is:

[0207]

[0208] The calculation method for the LH band in the first decomposition layer is:

[0209]

[0210] The calculation method for other frequency bands in the first decomposition layer and each frequency band in the second decomposition layer is the same as the above calculation method.

[0211] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0212] An image processing device is provided in an embodiment of the present disclosure. Figure 3 , Figure 3 FIG. 1 is a structural diagram of an image processing device according to an exemplary embodiment. Figure 3 As shown, the device comprises:

[0213] An extraction module 301 is configured to extract a red, green, and blue channel image and a white channel image from a target image;

[0214] A first determination module 302 is configured to determine a first gray component image of the red, green and blue channel images, and to determine a second gray component image of the white channel image;

[0215] The second determination module 303 is configured to determine first decomposition subband information of the first gray component image, and to determine second decomposition subband information of the second gray component image; the first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix;

[0216] A third determination module 304 is configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information;

[0217] The construction module 305 is configured to perform image reconstruction according to the third decomposition sub-band information to obtain a third gray component image, and construct a color image corresponding to the target image according to the third gray component image.

[0218] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0219] The second determination module 303 is further configured to determine the first decomposition sub-band information of the first gray component image and determine the second decomposition sub-band information of the second gray component image using the following method:

[0220] Using an image multi-scale decomposition method, determining first decomposition sub-band information of the first gray component image and determining second decomposition sub-band information of the second gray component image;

[0221] The number of decomposition layers in the first decomposition sub-band information and the number of frequency bands in each decomposition layer are the same.

[0222] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0223] The third determination module 304 is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0224] The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer;

[0225] For each frequency band under each decomposition layer in the third decomposition subband information, the frequency band coefficient matrix of the corresponding frequency band in the third decomposition subband information is calculated according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0226] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0227] The second determination module 303 is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0228] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0229] For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

[0230] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0231] The second determination module 303 is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0232] Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0233] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

[0234] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0235] The second determination module 303 is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0236] Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0237] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0238] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0239] The second determination module 303 is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0240] For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information;

[0241] For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix;

[0242] The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

[0243] The present disclosure provides an image processing device, which includes: Figure 3 The device shown, and:

[0244] The second determination module 303′ is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method:

[0245] Determining a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; and the eighth matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the second decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the second decomposition sub-band information;

[0246] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band;

[0247] The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band;

[0248] Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

[0249] An embodiment of the present disclosure provides an image processing device, a processor of the device;

[0250] a memory for storing processor-executable instructions;

[0251] Wherein, the processor is configured to execute the above method.

[0252] In an embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to execute the above method.

[0253] Figure 4 4 is a block diagram of an image processing apparatus 400 according to an exemplary embodiment. For example, the apparatus 400 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0254] Reference Figure 4 , the device 400 may include one or more of the following components: a processing component 402 , a memory 404 , a power component 406 , a multimedia component 408 , an audio component 410 , an input / output (I / O) interface 412 , a sensor component 414 , and a communication component 416 .

[0255] The processing component 402 generally controls the overall operation of the device 400, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 402 may include one or more processors 420 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 402 may include one or more modules to facilitate the interaction between the processing component 402 and other components. For example, the processing component 402 may include a multimedia module to facilitate the interaction between the multimedia component 408 and the processing component 402.

[0256] The memory 404 is configured to store various types of data to support operations on the device 400. Examples of such data include instructions for any application or method operating on the device 400, contact data, phone book data, messages, pictures, videos, etc. The memory 404 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0257] The power supply component 406 provides power to the various components of the device 400. The power supply component 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 400.

[0258] The multimedia component 408 includes a screen that provides an output interface between the device 400 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 408 includes a front camera and / or a rear camera. When the device 400 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0259] The audio component 410 is configured to output and / or input audio signals. For example, the audio component 410 includes a microphone (MIC), and when the device 400 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 404 or sent via the communication component 416. In some embodiments, the audio component 410 also includes a speaker for outputting audio signals.

[0260] I / O interface 412 provides an interface between processing component 402 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0261] The sensor assembly 414 includes one or more sensors for providing various aspects of status assessment for the device 400. For example, the sensor assembly 414 can detect the open / closed state of the device 400, the relative positioning of components, such as the display and keypad of the device 400, and the sensor assembly 414 can also detect the position change of the device 400 or a component of the device 400, the presence or absence of user contact with the device 400, the orientation or acceleration / deceleration of the device 400, and the temperature change of the device 400. The sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 414 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 414 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0262] The communication component 416 is configured to facilitate wired or wireless communication between the device 400 and other devices. The device 400 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 416 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 416 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0263] In an exemplary embodiment, the apparatus 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0264] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 404 including instructions, and the instructions can be executed by a processor 420 of the device 400 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0265] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0266] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An image processing method, characterized in that: include: Extract red, green, blue channel images and white channel image from the target image; Determine a first grayscale component image of the red, green and blue channel images, and determine a second grayscale component image of the white channel image; Determine first decomposition subband information of the first gray component image, and determine second decomposition subband information of the second gray component image; The first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; Determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information, so as to compensate the red, green and blue channel images by using the information of the white channel image; An image is reconstructed according to the third decomposition sub-band information to obtain a third gray component image, and a color image corresponding to the target image is constructed according to the third gray component image.

2. The image processing method according to claim 1, characterized in that: The determining of first decomposition subband information of the first gray component image and the determining of second decomposition subband information of the second gray component image include: Using an image multi-scale decomposition method, determining first decomposition sub-band information of the first gray component image and determining second decomposition sub-band information of the second gray component image; The number of decomposition layers in the first decomposition sub-band information and the number of frequency bands in each decomposition layer are the same.

3. The image processing method according to claim 1, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer; For each frequency band under each decomposition layer in the third decomposition subband information, the frequency band coefficient matrix of the corresponding frequency band in the third decomposition subband information is calculated according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

4. The image processing method according to claim 1 or 3, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information; For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

5. The image processing method according to claim 1 or 3, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

6. The image processing method according to claim 1 or 3, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

7. The image processing method according to claim 1 or 3, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information; For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

8. The image processing method according to claim 1 or 3, characterized in that: The determining the third decomposition subband information according to the first decomposition subband information and the second decomposition subband information comprises: Determining a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; and the eighth matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the second decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the second decomposition sub-band information; The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band; The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band; Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

9. An image processing device, characterized in that: include: An extraction module is configured to extract a red, green, blue channel image and a white channel image from a target image; A first determination module is configured to determine a first gray component image of the red, green and blue channel images, and to determine a second gray component image of the white channel image; A second determination module is configured to determine first decomposition sub-band information of the first gray component image, and to determine second decomposition sub-band information of the second gray component image; The first decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; the second decomposition subband information includes at least one decomposition layer, each decomposition layer includes at least one frequency band, and each frequency band corresponds to a frequency band coefficient matrix; a third determination module, configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information, so as to compensate the red, green and blue channel images by using the information of the white channel image; The construction module is configured to reconstruct an image according to the third decomposition sub-band information to obtain a third gray component image, and to construct a color image corresponding to the target image according to the third gray component image.

10. The image processing device according to claim 9, wherein: The second determination module is further configured to determine the first decomposition sub-band information of the first gray component image and determine the second decomposition sub-band information of the second gray component image using the following method: Using an image multi-scale decomposition method, determining first decomposition sub-band information of the first gray component image and determining second decomposition sub-band information of the second gray component image; The number of decomposition layers in the first decomposition sub-band information and the number of frequency bands in each decomposition layer are the same.

11. The image processing device according to claim 9, wherein: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: The same frequency band of the first decomposition sub-band information and the second decomposition sub-band information at the same decomposition layer is used as the frequency band corresponding to the third decomposition sub-band information at this decomposition layer; For each frequency band under each decomposition layer in the third decomposition subband information, the frequency band coefficient matrix of the corresponding frequency band in the third decomposition subband information is calculated according to the frequency band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the frequency band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

12. The image processing device according to claim 9 or 11, characterized in that: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information; For each frequency band in the third decomposition subband information except the set high frequency band, the coefficient value corresponding to each pixel point in the band coefficient matrix of each frequency band in the third decomposition subband information is determined to be the average value of the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the first decomposition subband information and the coefficient value of the corresponding pixel point in the band coefficient matrix of the corresponding frequency band in the second decomposition subband information.

13. The image processing device according to claim 9 or 11, characterized in that: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: Determine that a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a first matrix and a second matrix, wherein the first matrix is ​​the product of a weighted coefficient corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the second matrix is ​​the product of a weighted coefficient corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information in the same frequency band is 1, and the weighting coefficient corresponding to the second decomposition subband information in the set high frequency band is greater than the weighting coefficient corresponding to the frequency band other than the set high frequency band.

14. The image processing device according to claim 9 or 11, characterized in that: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: Determine a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band, which is the sum of a third matrix and a fourth matrix, wherein the third matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the fourth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

15. The image processing device according to claim 9 or 11, characterized in that: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: For the set high frequency band in the third decomposition sub-band information, determining the frequency band coefficient matrix of the set high frequency band in the second decomposition sub-band information as the corresponding frequency band coefficient matrix of the set high frequency band in the third decomposition sub-band information; For each frequency band except the set high frequency band in the third decomposition sub-band information, determining a frequency band coefficient matrix of the third decomposition sub-band information in each frequency band is the sum of a fifth matrix and a sixth matrix, the fifth matrix is ​​the product of the weighted coefficients corresponding to the first decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix, and the sixth matrix is ​​the product of the weighted coefficients corresponding to the second decomposition sub-band information on the corresponding frequency band and the frequency band coefficient matrix; The sum of the weighting coefficients corresponding to the first decomposition subband information and the second decomposition subband information on the same frequency band is 1; the weighting coefficient corresponding to the second decomposition subband information on the frequency band is negatively correlated with the number of decomposition layers to which the frequency band belongs.

16. The image processing device according to claim 9 or 11, characterized in that: The third determination module is further configured to determine third decomposition sub-band information according to the first decomposition sub-band information and the second decomposition sub-band information using the following method: Determine a band coefficient matrix for each frequency band in the third decomposition sub-band information, which is the sum of a seventh matrix and an eighth matrix, wherein the seventh matrix is ​​a dot product matrix of a band coefficient matrix for a corresponding frequency band in the first decomposition sub-band information and a weighted coefficient matrix for a corresponding frequency band in the first decomposition sub-band information; The eighth matrix is ​​a dot product matrix of a band coefficient matrix of a corresponding frequency band in the second decomposition sub-band information and a weight coefficient matrix of a corresponding frequency band in the second decomposition sub-band information; The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the first decomposition sub-band information is calculated based on the first variance corresponding to each pixel in the decomposition image of the first gray component image in the corresponding frequency band; The weight coefficient value of each pixel in the weight coefficient matrix of each frequency band in the second decomposition sub-band information is calculated based on the second variance corresponding to each pixel in the decomposition image of the second gray component image in the corresponding frequency band; Among them, the sum of the weighting coefficients corresponding to the same pixel point in the decomposition images of the first gray component image and the second gray component image in the same frequency band is 1; the weighting coefficient corresponding to each pixel point in the decomposition image of the first gray component image on each frequency band is positively correlated with the first variance corresponding to the corresponding pixel point, and the weighting coefficient corresponding to each pixel point in the decomposition image of the second gray component image on each frequency band is positively correlated with the second variance corresponding to the corresponding pixel point.

17. An image processing device, characterized in that: include: processor; memory for storing processor executable instructions; The processor is configured to execute the method of any one of claims 1 to 8.

18. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to execute the method of any one of claims 1 to 8.

Images