Video noise reduction device and method

Abstract

The invention discloses video noise reduction device and a video noise reduction method. The method comprises the following steps of: obtaining a brightness difference histogram of a current image by using a denoising result of a previous frame of image and a gradient magnitude histogram of the current image; carrying out noise level evaluation on the current image according to the brightness difference histogram; calculating the spatial distance of any two pixel points in the current image, so as to obtain the spatial similarity of the any two pixel points; carrying out denoising on the current image according to the spatial similarity; calculating a pixel time domain distance between any pixel point in the current image and the pixel point at the position corresponding to the previous frame of denoised image, and calculating the corresponding time domain similarity; carrying out three-dimensional recursive denoising on the video image according to the obtained time domain similarity, the spatial similarity denoising result and the previous frame of denoising result. By adopting the device and method disclosed by the invention, three-dimensional recursive denoising is carried out by using the pertinence of the pixel in space and time, so that strong complicated noise can be removed; an image detail can be kept; the stability of the denoising effect also can be ensured.

Description

technical field [0001] The present invention relates to a video noise reduction device and method, in particular to a video noise reduction device and method based on pixel similarity. Background technique [0002] Video noise reduction has always been one of the hotspots in image and video processing and computer vision research. The direct purpose of image and video denoising is to improve the noise-contaminated video image and solve the problem of image quality degradation caused by noise interference in actual images. Denoising can effectively improve the video image quality, increase the signal-to-noise ratio, and better reflect the information carried by the original video. A good denoising method will also improve the quality of subsequent video image processing, such as object segmentation, edge extraction, object tracking and recognition, etc. [0003] The key to denoising is to remove the interfering information in the signal while maintaining the integrity of us...

AI Technical Summary

Problems solved by technology

For example, there are many interference factors in the infrared image during the imaging process, which makes the infrared image noisy and the edges blurred

General denoising methods, such as mean filter, median filter, Wiener filter and wavelet soft and hard threshold method, etc., cannot achieve better denoising results.

Images