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Journal of Applied Remote Sensing

Dual-tree complex wavelet transform applied on color descriptors for remote-sensed images retrieval
Author(s): Houria Sebai; Assia Kourgli; Amina Serir
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Paper Abstract

This paper highlights color component features that improve high-resolution satellite (HRS) images retrieval. Color component correlation across image lines and columns is used to define a revised color space. It is designed to simultaneously take both color and neighborhood information. From this space, color descriptors, namely rotation invariant uniform local binary pattern, histogram of gradient, and a modified version of local variance are derived through dual-tree complex wavelet transform (DT-CWT). A new color descriptor called smoothed local variance (SLV) using an edge-preserving smoothing filter is introduced. It is intended to offer an efficient way to represent texture/structure information using an invariant to rotation descriptor. This descriptor takes advantage of DT-CWT representation to enhance the retrieval performance of HRS images. We report an evaluation of the SLV descriptor associated with the new color space using different similarity distances in our content-based image retrieval scheme. We also perform comparison with some standard features. Experimental results show that SLV descriptor allied to DT-CWT representation outperforms the other approaches.

Paper Details

Date Published: 16 October 2015
PDF: 17 pages
J. Appl. Remote Sens. 9(1) 095994 doi: 10.1117/1.JRS.9.095994
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Houria Sebai, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)
Assia Kourgli, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)
Amina Serir, Univ. des Sciences et de la Technologie Houari Boumediene (Algeria)


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