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Proceedings Paper

Contourlet spectral histogram for texture retrieval of remotely sensed imagery
Author(s): Qimin Cheng; Guangxi Zhu; Xianqiang Zhu
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Paper Abstract

In this paper, a progressive texture retrieval algorithm for remotely sensed imagery based on Contourlet spectral histogram is proposed. Contourlet transform is applied to extract texture features of remotely sensed imagery from different scales and different directions. Decomposed low-pass subband and high-pass subbands are used to realize coarse and fine retrieval respectively. The proposed algorithm not only utilizes the advantages of Contourlet on multiscale and multi-direction feature representation and extraction, but also utilizes the efficiency of spectral histogram on distributed statistical feature description. Experimental results prove that Contourlet Spectral Histogram provides a powerful tool for texture retrieval of remotely sensed imagery.

Paper Details

Date Published: 30 October 2009
PDF: 6 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981R (30 October 2009); doi: 10.1117/12.833964
Show Author Affiliations
Qimin Cheng, Huazhong Univ. of Science and Technology (China)
Guangxi Zhu, Huazhong Univ. of Science and Technology (China)
Xianqiang Zhu, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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