Open AccessResearch on Fast Estimation Method of Fuzzy Parameters for Motion Blurred Images
Author(s) -
Jing Luo,
Bo Tao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2029/1/012111
Subject(s) - computer vision , image restoration , motion blur , artificial intelligence , distortion (music) , kalman filter , wiener filter , computer science , motion estimation , deblurring , image (mathematics) , mathematics , image processing , algorithm , amplifier , computer network , bandwidth (computing)
Motion blur distortion is the most common type of image distortion in daily life. the research on motion-blurred image restoration technology has developed more mature. Classical algorithms such as Wiener filter and Kalman filter and various improved algorithms can achieve better results, but they take a long time and have great limitations in actual image restoration application scenarios. To solve this problem, this paper proposes an algorithm for fast restoration of image motion blur, an improved algorithm based on Randon transform to judge the image motion blur angle, and studies the algorithm for estimating the blur length under the condition that the blur angle is determined, and obtains two motion blur parameters of blurred image. Experimental results show that the fast image restoration method proposed in this paper has shorter time consumption, stronger anti-noise interference ability and better practicability.