A Degraded Image Restoration Approach Based on Pairs of Dictionaries Jointly Learning

A novel image restoration approach based on pairs of dictionaries jointly learning is proposed for the problem that the effect is weak to degraded images with traditional restoration approach based on dictionary learning. Firstly, the whole process and the key steps of restoration approach based on dictionary learning are analyzed in the basic frame of sparse decomposition and dictionary learning of images; And then, aiming at the limitation of the linear model of image restoration, a nonlinear frame based on pairs of dictionaries jointly learning is proposed, which solves the asymmetry problem of traditional dictionary learning technique in the process of degraded image restoration; Finally, the parameters of dictionaries model are estimated with a stochastic gradient descent algorithm, and the stability and speed of the algorithm is improved with a classical heuristic technique. The experimental results based on the isotropic and anisotropic kernels show that the proposed approach is competitive or even better than the state of the art approaches for non-blind image restoration.