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Proceedings Paper

Spatial and spectral coordinate super resolution of hyperspectral imagery based on redundant dictionary
Author(s): Suyu Wang; Zongxiang Zhang; Ying Wu
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Paper Abstract

Hyperspectral imagery has been widely used in various fields for its rich amount of feature information. The quality of hyperspectral imagery has been set higher requirements. As a result of the limitation of imaging semiconductor technology, hyperspectral image resolution needs to be improved by a signal processing method. This paper presents a recovery algorithm of spatial and spectral coordinate super-resolution of hyperspectral image based on redundant dictionary. Compared with the traditional image super-resolution restoration algorithm, the super-resolution restoration in the spectral of hyperspectral image was added on the basis of spatial resolution improvement. The original constraint was added in the algorithm and edges of reconstructed image were sharpened with the Maximum a Posterior. The results show this algorithm can effectively improve spatial and spectral resolution of the hyperspectral imagery.

Paper Details

Date Published: 9 December 2015
PDF: 8 pages
Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170E (9 December 2015); doi: 10.1117/12.2228374
Show Author Affiliations
Suyu Wang, Beijing Univ. of Technology (China)
Beijing Engineering Research Ctr. for IOT Software and System (China)
Zongxiang Zhang, Beijing Univ. of Technology (China)
Beijing Engineering Research Ctr. for IOT Software and System (China)
Ying Wu, Beijing Univ. of Technology (China)
Beijing Engineering Research Ctr. for IOT Software and System (China)


Published in SPIE Proceedings Vol. 9817:
Seventh International Conference on Graphic and Image Processing (ICGIP 2015)
Yulin Wang; Xudong Jiang, Editor(s)

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