Fuzzy vision image denoising algorithm based on Bayesian estimation

A fuzzy visual image denoising algorithm based on Bayesian estimation is proposed to address the problems of poor denoising performance and long denoising time in traditional image denoising algorithms.First, analyse the noise reduction requirements of fuzzy visual images, construct a visual image degradation model, and obtain fuzzy visual images.Then, analyse the spectrum of the acquired fuzzy visual image, preprocess the spectrum signal by adding a window function, and detect the edge of the fuzzy visual image according to the preprocess result to supplement the fuzzy edge.Based on the supplemented blurred visual image edges, Bayesian estimation is used for image denoising to improve the image denoising effect.The experimental results show that the visual image obtained by the proposed method is relatively clear and has high image quality, indicating that the denoising effect of the algorithm is good and the denoising time is short.