PSF Estimation Method of Simple-Lens Camera Using Normal Sinh-Arcsinh Model Based on Noise Image Pairs

With the development of computational photography, single-lens camera combined with corresponding image deblurring algorithm is gradually becoming a new research direction, replacing complex modern optical imaging system such as single lens reflex (SLR) camera. For camera, Point Spread Function (PSF) estimation accuracy will directly affect restoration effect. In this paper, we designed simple-lens cameras one, two and three lenses, respectively, propose robust accurate PSF method The key point to obtain blur clear pairs, which are necessary for non-blind deconvolution estimation. Considering structure characteristic take picture original displayed on computer screen get pairs through corner detection color correction made remove distortion. addition, few studies have shown that simple close spatially deformed wedge, so use more reasonable Normal Sinh-Arcsinh (NSAS) model fit kernel its parameters by Powell algorithm. experiment results space-variant estimated proposed achieves better performance than compared methods both qualitatively quantitatively.