Fuzzy Image Restoration Algorithm Based on Machine Vision Technology

Fuzzy image refers to the problems of image blur, noise, and distortion caused by many situations during the acquisition, transmission and processing. Restoration of fuzzy images is an important problem in the field of image processing and computer vision. This study tells about a kind of fuzzy image recovery algorithm with machine vision technology, and realizes the automatic restoration of fuzzy image by using the L-R algorithm. Specifically, We used experimental comparison to compare the advantages and disadvantages of L-R algorithm and traditional algorithm when dealing with fuzzy images, and apply the method to image restoration in actual scenes and compare its parameters. Experimental data shows that the parameters of fuzzy image restoration based on L-R algorithm are 0.0521, 0.2705, and 0.1654 on MSE, RMSE, and PSNR, which are better than traditional inverse deconvolution algorithms. It proves that the fuzzy image recovery algorithm based on machine vision technology has higher recovery effect and better robustness. The algorithm can adjust parameters adaptively, and is suitable for fuzzy image restoration of different types and degrees.