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Depth image super-resolution using multi-dictionary sparse representation

Conference Paper


Abstract


  • 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.

Publication Date


  • 2013

Citation


  • H. Zheng, A. Bouzerdoum & S. L. Phung, "Depth image super-resolution using multi-dictionary sparse representation," in 20th IEEE International Conference on Image Processing (ICIP 2013), 2013, pp. 957-961.

Scopus Eid


  • 2-s2.0-84897748088

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2339

Has Global Citation Frequency


Start Page


  • 957

End Page


  • 961

Place Of Publication


  • United States

Abstract


  • 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.

Publication Date


  • 2013

Citation


  • H. Zheng, A. Bouzerdoum & S. L. Phung, "Depth image super-resolution using multi-dictionary sparse representation," in 20th IEEE International Conference on Image Processing (ICIP 2013), 2013, pp. 957-961.

Scopus Eid


  • 2-s2.0-84897748088

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2339

Has Global Citation Frequency


Start Page


  • 957

End Page


  • 961

Place Of Publication


  • United States