In this paper, the blind recovery of gray image is studied in this paper, and two different images are introduced The original method. One is the error parameter analysis method, which is suitable for the identification of parameters Point diffusion functions, such as linear motion model and Gauss model, then determine the degraded image according to the estimated parameters The diffusion function is used to reconstruct the degraded image using conventional recovery algorithm, such as the wiener filtering method Another nonnegative support domain constraint recursive inverse filtering (NAS- R) algorithm is presented in this paper Based on the idea of regularization, the improved algorithm of NAS-RIF is proposed and the algorithm is corresponding The performance effect is simulated and analyzed. 1. Image denoising MATLAB simulation program. M 2. The image point extension function retrieves MATLAB simulation program 3. Constraint least squares image restoration MATLAB simulation program. M

Packet : 93317447psf.rar filelist
数字图像的盲复原研究\图像去噪MATLAB仿真程序.m
数字图像的盲复原研究\图像点扩展函数获取MATLAB仿真程序.m
数字图像的盲复原研究\图像的盲复原研究.nh
数字图像的盲复原研究\约束最小二乘法图像复原MATLAB仿真程序.m
数字图像的盲复原研究

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