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Journal of Applied Remote Sensing • Open Access

Improved color texture descriptors for remote sensing image retrieval
Author(s): Zhenfeng Shao; Weixun Zhou; Lei Zhang; Jihu Hou

Paper Abstract

Texture features are widely used in image retrieval literature. However, conventional texture features are extracted from grayscale images without taking color information into consideration. We present two improved texture descriptors, named color Gabor wavelet texture (CGWT) and color Gabor opponent texture (CGOT), respectively, for the purpose of remote sensing image retrieval. The former consists of unichrome features computed from color channels independently and opponent features computed across different color channels at different scales, while the latter consists of Gabor texture features and opponent features mentioned above. The two representations incorporate discriminative information among color bands, thus describing well the remote sensing images that have multiple objects. Experimental results demonstrate that CGWT yields better performance compared to other state-of-the-art texture features, and CGOT not only improves the retrieval results of some image classes that have unsatisfactory performance using CGWT representation, but also increases the average precision of all queried images further. In addition, a similarity measure function for proposed representation CGOT has been defined to give a convincing evaluation.

Paper Details

Date Published: 24 July 2014
PDF: 13 pages
J. Appl. Rem. Sens. 8(1) 083584 doi: 10.1117/1.JRS.8.083584
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Zhenfeng Shao, Wuhan Univ. (China)
Weixun Zhou, Wuhan Univ. (China)
Lei Zhang, Wuhan Univ. (China)
Jihu Hou, Wuhan Univ. (China)

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