Video denoising method and calculation equipment

A video and video acquisition technology, applied in the field of image processing, can solve problems such as blurred edges, difficulty in effectively removing image noise, and inability to solve time-domain flicker noise well
CN107454284AActive Publication Date: 2017-12-08XIAMEN MEITUZHIJIA TECH

Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XIAMEN MEITUZHIJIA TECH
Publication Date
2017-12-08

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Abstract

The invention discloses a video denoising method. The method includes the steps of obtaining at least one adjacent frame of a frame to be denoised in a video sequence; performing time domain denoising on each pixel point of the frame to be denoised, the time domain denoising including the steps of, for each adjacent frame of the frame to be denoised, obtaining matched pixel points of the pixel points of the frame to be denoised on the adjacent frame, and calculating the weights of the matched pixel points; and based on the weights of the obtained matched pixel points of the pixel points of the frame to be denoised on each adjacent frame, calculating the weighted average of the pixel points of the frame to be denoised and the matched pixel points thereof, so as to obtain pixel values of the pixel points of the frame to be denoised after time domain denoising. The invention also discloses corresponding calculation equipment and a computer storage medium.
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Description

technical field

[0001] The invention relates to the technical field of image processing, in particular to a video denoising method and computing equipment. Background technique

[0002] In the application scenario of image or video acquisition, the acquired image will inevitably have signal noise. For example, pictures or videos taken in scenes such as night usually have relatively obvious noise. Image denoising is a very important link in image processing (single image processing or video frame sequence processing). The main problem of denoising is how to effectively remove the temporal domain and spatial domain noise while effectively preserving the boundary texture details of the image from being destroyed.

[0003] At present, the mainstream processing method is to perform bilateral filtering in the spatial domain and mean filtering in the time domain. However, the disadvantage of this method is that it cannot guarantee the consistency of the filtering strength of adja...

Claims

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