Structural Dissimilarity Learning Dictionary via Block Feature Coding for Image Super-Resolution

In this paper, we present an improved single image super-resolution method. The improvements are mainly attributed to block feature coding (BFC) that is to select structurally dissimilar image patches by coding the edge and direction features of image patches. A structural dissimilarity learning dictionary (SDLD-BFC) pair are trained on a small training image patches set. Numerous experiments demonstrate efficient SDLD-BFC training and robust SDLDBFC method. Compared with other SR methods, SDLD-BFC significantly improves efficiency, while recovering good edge and texture.