title: PSF estimation via gradient domain correlation.
abstract: This paper proposes an efficient method to estimate the point spread function (PSF) of a blurred image using image gradients spatial correlation. A patch-based image degradation model is proposed for estimating the sample covariance matrix of the gradient domain natural image. Based on the fact that the gradients of clean natural images are approximately uncorrelated to each other, we estimated the autocorrelation function of the PSF from the covariance matrix of gradient domain blurred image using the proposed patch-based image degradation model. The PSF is computed using a phase retrieval technique to remove the ambiguity introduced by the absence of the phase. Experimental results show that the proposed method significantly reduces the computational burden in PSF estimation, compared with existing methods, while giving comparable blurring kernel.
authors.forename: Wei
authors.initials: W
authors.lastname: Hu
authors.forename: Jianru
authors.initials: J
authors.lastname: Xue
authors.forename: Nanning
authors.initials: N
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic