Image Restoration Through Dictionary Learning and Sparse Representation

Abstract

Based on the content dual-dictionary learning and sparse representation, we put forward a novel method of image restoration. This method can improve the adaptive ability of the image. To restore the image, the dual-dictionary is trained with sparse representation. Comparing with the traditional dictionary learning algorithm, the method in this paper can capture more high-frequency information and enhance the image quality further in image reconstruction. The experimental results show that the proposed method is useful for image restoration and much better than other methods.

Recent Development of Dual-Dictionary Learning Approach in Medical Image Analysis and Reconstruction

“…Similar to HaiChaos' work, Wang et al also applied DDL in image restoration [ 38 ]. They solved the problem of restoring the lost part of high-frequency detail information of images.…”