Quotient Set-based Nonlinear Manifold for Image Restoration

In this paper we propose a patch-wise coarse-to-fine algorithm for image restoration using the manifold way of visual perception. All undistorted image patches are supposed to lie on a quotient set-based nonlinear manifold, and restoration of each degraded image patch can be implemented by projecting it to a locally linear region of such nonlinear manifold. The details of the original image can be learned from the undistorted training samples. Moreover, there is no need for us to assume that the degradation function is linear or to estimate some parameters of the blurs and noises beforehand. Experimental results demonstrate the effectiveness of the proposed method