Video image 3D noise reduction method, computer device and computer readable storage medium

Abstract

The invention provides a video image 3D noise reduction method, a computer device and a computer readable storage medium. The method comprises the steps of obtaining a current video frame and a previous video noise reduction frame; Performing time domain filtering according to the current video frame and the previous video noise reduction frame to obtain a time domain filtering weight of each pixel point of the current video frame; Performing spatial domain filtering based on direction statistics on the current video frame to obtain a spatial domain filtering result of each pixel point of thecurrent video frame; And carrying out weighted fusion on the spatial domain filtering result and the previous video noise reduction frame according to the time domain filtering weight to obtain a video noise reduction frame of the current video frame. The computer device is provided with a processor, and when the processor executes a program, the video image 3D noise reduction method can be achieved. A computer program is stored in the computer readable storage medium and used for achieving the video image 3D noise reduction method. By applying the method, common Gaussian noise and compressionnoise of the video are remarkably reduced, and meanwhile few hardware resources such as storage space and bandwidth are occupied.

Description

technical field [0001] The present invention relates to the technical field of digital video processing, in particular to a method for 3D noise reduction of video images, a computer device applying the method, and a computer-readable storage medium applying the method. Background technique [0002] In the process of video shooting, storage, compression, transmission, etc., there are inevitably various interference factors, which lead to the generation of video noise, including Gaussian noise, compression noise, etc., which reduce the quality of video images. Video noise reduction technology uses the pixel correlation of images in time domain or space domain and the randomness of noise to reduce noise. It is required to ensure that the original details or texture of the image are not blurred or blurred when reducing noise and improving the cleanliness of the image. destroy. [0003] The existing video noise reduction schemes can be mainly divided into the following categorie...

AI Technical Summary

Problems solved by technology

The implementation cost of this type of solution is lower than the above two types, but the noise reduction effect is relatively weak, and it is prone to adverse phenomena such as smearing or image blur

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