An image processing method, apparatus, electronic device, computer-readable storage medium, and computer program product
By sliding a window in the image and calculating the information density to select the sub-image with the highest density for denoising, the problem of low denoising efficiency in the prior art is solved, and the efficiency and quality of image processing are improved.
CN122415369APending Publication Date: 2026-07-17TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TENCENT TECHNOLOGY (SHENZHEN) CO LTD
- Filing Date
- 2025-01-17
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies suffer from low noise reduction efficiency when performing region-based image processing, which affects the overall efficiency of image processing.
Method used
By sliding a pre-selected window in the image, M first sub-images are defined, and the information density of each sub-image is calculated. The sub-image with the highest information density is selected for denoising, and finally combined into a second image.
Benefits of technology
It improves the efficiency of image denoising and the overall efficiency of image processing, ensures that the selected sub-images contain complete information, and reduces the amount of denoising processing.
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Smart Images
Figure CN122415369A_ABST
Abstract
The application provides an image processing method and device, electronic equipment, computer readable storage medium and computer program product; the image processing method comprises: sliding a preselected window in a first image, traversing the first image to define 0 first sub-images, wherein 0 is an integer greater than 0, and the 0 first sub-images are each defined by the preselected window sliding a preset step length in turn, and the preset step length is less than the length of the preselected window in the sliding direction; obtaining information density corresponding to the 0 first sub-images respectively to obtain 0 information densities; based on the maximum information density in the 0 information densities, selecting 1 first sub-image from the 0 first sub-images, the union of the 1 first sub-image is the first image, and 1 is an integer less than 0; denoising the 1 first sub-image to obtain 1 second sub-image; and combining the 1 second sub-image into a second image. Through the application, the efficiency of image processing can be improved.
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