Image super-resolution based on multi-space sparse representation

Authors:
Guodong Jing;Yunhui Shi;Dehui Kong;Wenpeng Ding;Baocai Yin
Affiliations:
Beijing University of Technology, Beijing, China;Beijing University of Technology, Beijing, China;Beijing University of Technology, Beijing, China;Beijing University of Technology, Beijing, China;Beijing University of Technology, Beijing, China
Venue:
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Year:
2010

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Abstract

Sparse representation provides a new method of generating a super-resolution image from a single low resolution input image. An over-complete base for sparse representation is an essential part of such methods. However discovering the over-complete base with efficient representation from a large amount of image patches is a difficult problem. We make efforts in sparse representation and its implementation to solve the problem. In the representation, image patches are decomposed into two structure and texture components represented by the over-complete bases of their own spaces so that their high-level features can be captured by the bases. In the implementation, a prior knowledge about low resolution images generation is combined to the typical base construction for high construction quality. Finally a super-resolution construction based on multi-space sparse representation is proposed. Experiment results demonstrate that the proposed method significantly improve the PSNR and visual quality of reconstructed high-resolution image.