PSF Estimation via Covariance Matching
نویسندگان
چکیده
This paper proposes a new covariance matching based technique for blurred image PSF (point spread function) estimation. A patch based image degradation model is proposed for the covariance matching estimation framework. A robust covariance metric which is based on Riemannian manifold is adapted to measure the distance between covariance matrices. The optimal PSF is computed by minimizing the dissimilarity between the covariance matrix of the blurred image patches and the theoretical covariance matrix which is based on autoregressive image model. Experimental results show that the proposed method produces promising PSF estimation results.
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