期刊名称：International Journal of Electronics, Communication and Soft Computing Science and Engineering
印刷版ISSN：2277-9477
出版年度：2015
卷号：4
期号：Special 3
出版社：IJECSCSE
摘要：Learning based image super - resolution metho d is used to reconstruct high - frequency (HF) details from the prior model trained by a set of high - (HR) and low - resolution (LR) image patches. In this paper, newly proposed novel image super - resolution method via dual - dictionary learning and sparse represe ntation, which consists of the main dictionary learning and the residual dictionary learning, to recover MHF and RHF respectively. The experimental results on test images validate that by employing the proposed method, more image details can be recovered an d much better results can be achieved than the state - of - the - art algorithms in terms of both PSNR and visual perception
