Blind image deconvolution based on robust stable edge prediction

This paper proposes a robust blind deconvolution method for removing a uniform blur from microscopy images. For the estimation of the kernel - point spread function (PSF) - the stable edge is estimated using a fuzzy edge prediction method. Based on the estimated stable edges, optimizing a blurring objective function leads to a closed form for the estimation of a kernel and latent image. In comparison with existing deconvolution methods based on iterative optimization, the proposed method with a closed-form solution produces a significant decrease in processing time, which is an important barrier in applying deconvolution methods to real-world applications. Experimental results demonstrate the robustness and high efficiency of the proposed method for diverse microscopy images.