Block-blur-kernel-set-based heterogeneous video blind deblurring method

Abstract

The invention, which belongs to the technical field of video processing, relates to a block-blur-kernel-set-based heterogeneous video blind deblurring method. The method comprises the following steps: detecting a blurred frame according to a gradient size of a video frame image; calculating block homograph according to feature matching of a clear frame and a blurred frame; carrying out discrete sampling of the block homograph to realize blurring approximation motion and calculating a velocity parameter of the blurring motion based on approximation error optimization; according to the blurring motion velocity, obtaining burring kernels corresponding to all blocks and calculating clear blocks by using deconvolution; and splicing the clear blocks to obtain a clear frame image, thereby removing blurred frames. Compared with the prior method, the provided method is characterized in that a blurring motion of a video frame is described by using a plurality of blur kernels; no initial value needs to be set during calculation, thereby enhancing the robustness; heterogeneous video blurring processing becomes efficient; requirements on the clear area of the video are low; and the application range is widened.

Description

Technical field: [0001] The invention relates to a video blind deblurring method, in particular to a non-uniform video blind deblurring method based on block fuzzy kernel sets, and belongs to the technical field of video processing. Background technique: [0002] With the popularization of digital cameras, video shooting has become an important activity in people's daily life, and has important applications in home entertainment, film and television production, production security and so on. However, due to the limitations of the environment and users during video shooting, problems such as blurred images inevitably exist in the captured video, which affects the viewing experience of the human eye and further processing in the later stage. [0003] Scholars at home and abroad have done a lot of basic research on video deblurring, which has high application value. Commonly used video deblurring methods mainly include two categories: methods based on blur kernel optimization ...

AI Technical Summary

Problems solved by technology

However, this method has high requirements on the distribution of clear areas in the video, that is, if the relevant areas on the blurred frame do not have corresponding clear areas on other frames, this method will not be able to perform deblurring processing, thus affecting the final video quality.

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