Description: 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
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