A fuzzy K-nearest-neighbor algorithm to blind image deconvolution

This paper proposes an adaptive blind image deconvolution scheme based on fuzzy K-nearest-neighbor (FKNN) algorithm. It is well known that most point-spread functions (PSFs) satisfy up to a certain degree of parametric structure. The method incorporates such knowledge about the PSF structure by estimating the PSF according to its K nearest neighbors. Through a process of neighbor generation, model matching, and fuzzy weighted mean filtering, FKNN provides a robust estimate for the blur. This further improves the convergence performance in blind deconvolution process. Experimental results show that it is effective in restoring degraded images where there is little prior knowledge about the blur.