Science and Technology Studies Commons^™

Depth Image Super-Resolution Using Multi-Dictionary Sparse Representation, Haoheng Zheng, Abdesselam Bouzerdoum, Son Lam Phung

Haoheng Zheng

In this paper, we propose a new depth super-resolution technique based on multiple dictionary learning. A novel dictionary selection method using basis pursuit is proposed to generate multiple dictionaries adaptively. A sparse representation of each low-resolution input patch is derived based on the learned dictionaries, and then used to reconstruct the corresponding high-resolution patch. Experimental results are presented which show that the proposed multi-dictionary scheme outperforms existing depth super-resolution methods.