# US 2022/0036518 A1 · Method for processing image, electronic device and storage medium > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0036518 A1 - Document ID: US20220036518A1 - Status: Published application - Kind: A1 - Application number: 17/244,790 - Filed: 2021-04-29 - Published: 2022-02-03 - Earliest claimed: 2020-07-31 - Assignees: Beijing Xiaomi Mobile Software Co., Ltd. - Applicants: Beijing Xiaomi Mobile Software Co., Ltd. - Inventors: Liangqi GUO - Web page: https://patentgrep.com/patent/US20220036518A1 ## CPC - G06T 5/73: Deblurring; Sharpening - G06T 5/20: using local operators - G06T 5/50: using two or more images, e.g. averaging or subtraction - G06T 5/70: Denoising; Smoothing - G06T 2207/20024: Filtering details - G06T 2207/20182: Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering - G06T 2207/20221: Image fusion; Image merging - G06T 2207/20224: Image subtraction - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract An image is obtained. A denoised image is determined by performing denoising processing on the image based on a preset denoising method. At least two frequency information components of the denoised image are obtained by performing filter processing on a preset region image of the denoised image on at least two preset frequency levels. A sharpened image is obtained by performing superposition processing on the denoised image based on at least two frequency information components and a preset adjustment parameter. A target image is determined based on the sharpened image. ## Claims ### Claim 1 A method for processing an image, applied to an electronic device, comprising: obtaining an image; determining a denoised image by performing denoising processing on the image based on a preset denoising method; obtaining at least two frequency information components of the denoised image by performing filter processing on a preset region image of the denoised image on at least two preset frequency levels, wherein the at least two frequency information components correspond to at least two preset frequency levels respectively; obtaining a sharpened image by performing superposition processing on the denoised image based on the at least two frequency information components and a preset adjustment parameter; and determining a target image based on the sharpened image. ### Claim 2 (depends on 1) The method of claim 1, wherein obtaining the at least two frequency information components of the denoised image comprises: obtaining at least two of a high-frequency information component, an intermediate-high-frequency information component, and an intermediate-frequency information component of the denoised image by performing the filter processing on the preset region image of the denoised image using at least two of a high-pass filter, an intermediate-high-pass filter, and a band-pass filter, wherein the at least two information components correspond to the at least two filters respectively. ### Claim 3 (depends on 1) The method of claim 1, wherein, the preset region image comprises an edge image and/or a detail region image of the denoised image. ### Claim 4 (depends on 1) The method of claim 1, wherein obtaining the sharpened image comprises: for each of the at least two frequency information components, adjusting a gain parameter contained in the preset adjustment parameter and corresponding to the frequency information component, to determine at least two frequency optimization information components corresponding to the at least two frequency information components; and obtaining the sharpened image by superimposing the at least two frequency optimization information components onto the denoised image. ### Claim 5 (depends on 4) The method of claim 4, wherein obtaining the sharpened image by superimposing the at least two frequency optimization information components onto the denoised image comprises: determining a component threshold corresponding to each frequency optimization information component; and determining the sharpened image by superimposing frequency optimization information components corresponding to the component threshold sequentially onto the denoised image within the component threshold. ### Claim 6 (depends on 1) The method of claims 1, wherein, the preset adjustment parameter comprises at least one of a brightness parameter, a spatial frequency parameter, a brightness contrast parameter, a local histogram parameter, a local pixel method parameter, and a local pixel uniformity parameter. ### Claim 7 (depends on 1) The method of claim 1, further comprising: determining a differential image based on the image and the denoised image; wherein, the differential image comprises image detail information; wherein determining the target image based on the sharpened image comprises: determining the target image by performing image processing based on the sharpened image, noise information of the image, and the differential image. ### Claim 8 (depends on 7) The method of claim 7, wherein determining the differential image based on the image and the denoised image comprises: obtaining the differential image by subtracting a pixel value of each pixel in the denoised image from a pixel value of a corresponding pixel in the image. ### Claim 9 (depends on 7) The method of claim 7, wherein determining the target image by performing the image processing based on the sharpened image, the noise information, and the differential image comprises: determining the image detail information based on the differential image and the noise information; determining a weight of each pixel in the image detail information; determining a supplementary pixel parameter based on a pixel parameter of each pixel in the image detail information and the weight corresponding to the pixel; and obtaining the target image by superimposing supplementary pixels onto the sharpened image based on the supplementary pixel parameter. ### Claim 10 An electronic device, comprising: a processor; a memory, configured to store instructions executable by the processor; wherein, the processor is configured to: obtain an image; determine a denoised image by performing denoising processing on the image based on a preset denoising method; obtain at least two frequency information components of the denoised image by performing filter processing on a preset region image of the denoised image on at least two preset frequency levels, wherein the at least two frequency information components correspond to at least two preset frequency levels respectively; obtain a sharpened image by performing superposition processing on the denoised image based on the at least two frequency information components and a preset adjustment parameter; and determine a target image based on the sharpened image. ### Claim 11 (depends on 10) The electronic device of claim 10, wherein the processor is further configured to: obtain at least two of a high-frequency information component, an intermediate-high-frequency information component, and an intermediate-frequency information component of the denoised image by performing the filter processing on the preset region image of the denoised image using at least two of a high-pass filter, an intermediate-high-pass filter, and a band-pass filter, wherein the at least two information components correspond to the at least two filters respectively. ### Claim 12 (depends on 10) The electronic device of claim 10, wherein, the preset region image comprises an edge image and/or a detail region image of the denoised image. ### Claim 13 (depends on 10) The electronic device of claim 10, wherein the processor is further configured to: for each of the at least two frequency information components, adjust a gain parameter contained in the preset adjustment parameter and corresponding to the frequency information component, to determine at least two frequency optimization information components corresponding to the at least two frequency information components; and obtain the sharpened image by superimposing the at least two frequency optimization information components onto the denoised image. ### Claim 14 (depends on 13) The electronic device of claim 13, wherein the processor is further configured to: determine a component threshold corresponding to each frequency optimization information component; and determine the sharpened image by superimposing frequency optimization information components corresponding to the component threshold sequentially onto the denoised image within the component threshold. ### Claim 15 (depends on 10) The electronic device of claim 10, wherein the preset adjustment parameter comprises at least one of a brightness parameter, a spatial frequency parameter, a brightness contrast parameter, a local histogram parameter, a local pixel method parameter, and a local pixel uniformity parameter. ### Claim 16 (depends on 10) The electronic device of claim 10, wherein the processor is further configured to: determine a differential image based on the image and the denoised image; wherein, the differential image comprises image detail information; and determine the target image by performing image processing based on the sharpened image, noise information of the image, and the differential image. ### Claim 17 (depends on 16) The electronic device of claim 16, wherein the processor is further configured to: obtain the differential image by subtracting a pixel value of each pixel in the denoised image from a pixel value of a corresponding pixel in the image. ### Claim 18 (depends on 16) The electronic device of claim 16, wherein the processor is further configured to: determine the image detail information based on the differential image and the noise information; determine a weight of each pixel in the image detail information; determine a supplementary pixel parameter based on a pixel parameter of each pixel in the image detail information and the weight corresponding to the pixel; and obtain the target image by superimposing supplementary pixels onto the sharpened image based on the supplementary pixel parameter. ### Claim 19 A non-transitory computer readable storage medium, wherein when instructions stored on the storage medium are executed by an electronic device, the electronic device is caused to execute a method for processing an image, the method comprising: obtaining an image; determining a denoised image by performing denoising processing on the image based on a preset denoising method; obtaining at least two frequency information components of the denoised image by performing filter processing on a preset region image of the denoised image on at least two preset frequency levels, wherein the at least two frequency information components correspond to at least two preset frequency levels respectively; obtaining a sharpened image by performing superposition processing on the denoised image based on the at least two frequency information components and a preset adjustment parameter; and determining a target image based on the sharpened image. ### Claim 20 (depends on 19) The non-transitory computer readable storage medium of claim 19, wherein obtaining the at least two frequency information components of the denoised image comprises: obtaining at least two of a high-frequency information component, an intermediate-high-frequency information component, and an intermediate-frequency information component of the denoised image by performing the filter processing on the preset region image of the denoised image using at least two of a high-pass filter, an intermediate-high-pass filter, and a band-pass filter, wherein the at least two information components correspond to the at least two filters respectively.