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CN-116012244-B - Image denoising method based on image multi-scale information and electronic equipment

CN116012244BCN 116012244 BCN116012244 BCN 116012244BCN-116012244-B

Abstract

The image denoising method based on the image multi-scale information comprises the steps of obtaining an image to be processed, constructing an image pyramid based on the image to be processed, searching associated pixel points related to the current pixel points from the image pyramid for each current pixel point to be filtered in the image to be processed, calculating spatial filtering weights of the associated pixel points based on the current pixel points and the associated pixel points, obtaining a filtering result of the current pixel points based on the spatial filtering weights, and obtaining a denoising result of the image to be processed based on the filtering result of each current pixel point. According to the method and the device, the original single-scale pixel point matching is expanded to multiple scales through the image pyramid by constructing the image pyramid, so that the multi-scale information of the image can be used, more points can participate in the spatial filtering, the effect of the spatial filtering is enhanced, the image noise can be removed better, and the image detail information can be reserved better.

Inventors

  • HUANG FANG

Assignees

  • 成都西纬科技有限公司

Dates

Publication Date
20260512
Application Date
20221229

Claims (8)

  1. 1. An image denoising method based on image multi-scale information, the method comprising: acquiring an image to be processed, and constructing an image pyramid based on the image to be processed; Searching the associated pixel points related to the current pixel points from the image pyramid aiming at each current pixel point to be filtered in the image to be processed, wherein the searching comprises the steps of calculating the pixel points corresponding to the current pixel points in each layer of the image pyramid as central pixel points; Calculating the spatial filtering weight of the associated pixel point based on the current pixel point and the associated pixel point, wherein the spatial filtering weight of each associated pixel point is calculated based on the absolute value of the pixel value difference value and the intensity value of participation of the pixel point of each layer of the predefined image pyramid in spatial filtering; Obtaining a filtering result of the current pixel point based on the spatial filtering weight; And obtaining a noise reduction result of the image to be processed based on the filtering result of each current pixel point.
  2. 2. The method of claim 1, wherein the constructing an image pyramid based on the image to be processed comprises: defining the layer number of the image pyramid, wherein the image pyramid comprises a first layer and other layers; assigning the image to be processed to the first layer; and convolving the image to be processed on the basis of the defined filtering check on the other layers, and downsampling and then assigning the image to the other layers.
  3. 3. The method according to claim 2, wherein the method further comprises: Initializing a vector with a length equal to the number of layers of the image pyramid for storing the layers of the image pyramid.
  4. 4. A method according to claim 3, wherein said obtaining a filtering result of the current pixel point based on the spatial filtering weight comprises: Calculating the spatial filtering weight of each associated pixel point and calculating the weighted pixel value of each associated pixel point; and taking the ratio of the sum of weighted pixel values of all the associated pixel points to the sum of all the spatial filtering weights as a filtering result of the current pixel point.
  5. 5. The method according to claim 1, wherein the image to be processed is a gray scale image or a luminance image.
  6. 6. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program to be run by the processor, which when run by the processor causes the processor to perform the image denoising method based on image multi-scale information according to any one of claims 1-5.
  7. 7. A storage medium having stored thereon a computer program which, when executed, causes a processor to perform the image denoising method based on image multi-scale information according to any one of claims 1-5.
  8. 8. A computer program product, characterized in that the computer program product comprises a computer program which, when run by a processor, causes the processor to perform the image denoising method based on image multi-scale information as claimed in any one of claims 1-5.

Description

Image denoising method based on image multi-scale information and electronic equipment Technical Field The application relates to the technical field of image noise reduction, in particular to an image noise reduction method based on image multi-scale information and electronic equipment. Background Noise is a significant cause of image disturbance. In practical applications, an image may have various noises, and these noises may be generated during transmission or quantization. The common spatial filtering algorithm based on the spatial pixel similarity often influences the accuracy of matching by noise when similar pixel matching is carried out, influences the effect of spatial filtering, and further influences the effect of image noise reduction. Disclosure of Invention The present application has been made to solve the above-described problems. According to one aspect of the application, an image denoising method based on image multi-scale information is provided, and the method comprises the steps of obtaining an image to be processed, constructing an image pyramid based on the image to be processed, searching associated pixel points related to the current pixel points from the image pyramid aiming at each current pixel point to be filtered in the image to be processed, calculating spatial filtering weights of the associated pixel points based on the current pixel points and the associated pixel points, obtaining a filtering result of the current pixel points based on the spatial filtering weights, and obtaining a denoising result of the image to be processed based on the filtering result of each current pixel point. In one embodiment of the application, the image pyramid is constructed based on the image to be processed, and comprises the steps of defining the layer number of the image pyramid, wherein the image pyramid comprises a first layer and other layers, assigning the image to be processed to the first layer, convolving the image to be processed based on a defined filtering check to the other layers, and assigning the image to the other layers after downsampling. In one embodiment of the application, the method further comprises initializing a vector having a length equal to the number of layers of the image pyramid for storing the layers of the image pyramid. In one embodiment of the application, the searching of the associated pixel points related to the current pixel point from the image pyramid comprises the steps of calculating the pixel point corresponding to the current pixel point in each layer of the image pyramid as a central pixel point, and taking the central pixel point in each layer of the image pyramid as a center and taking all the pixel points in a defined spatial domain noise reduction radius as the associated pixel points related to the current pixel point. In one embodiment of the application, the calculating the spatial filtering weight of the associated pixel point based on the current pixel point and the associated pixel point comprises calculating a pixel value difference value of each associated pixel point and the current pixel point, and calculating the spatial filtering weight of each associated pixel point based on an absolute value of the pixel value difference value. In one embodiment of the application, the filtering result of the current pixel point is obtained based on the spatial filtering weight, and the filtering result of the current pixel point comprises the steps of calculating a weighted pixel value of each associated pixel point according to the spatial filtering weight of each associated pixel point, and taking the ratio of the sum of the weighted pixel values of all the associated pixel points to the sum of all the spatial filtering weights as the filtering result of the current pixel point. In one embodiment of the present application, the image to be processed is a gray scale image or a brightness image. According to another aspect of the present application, there is provided an electronic device including a memory and a processor, the memory having stored thereon a computer program to be executed by the processor, which when executed by the processor, causes the processor to perform the above-described image denoising method based on image multi-scale information. According to the image noise reduction device based on the image multi-scale information, the image noise reduction device comprises a pyramid construction module, a weight calculation module and a filtering module, wherein the pyramid construction module is used for acquiring an image to be processed and constructing an image pyramid based on the image to be processed, the weight calculation module is used for searching a relevant pixel point related to the current pixel point from the image pyramid aiming at each current pixel point to be filtered in the image to be processed, calculating spatial filtering weights of the relevant pixel points based on the current pixel point and the re