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Proceedings Paper

SAR image compression based on multibandelets and geometric flow optimization
Author(s): Shuyuan Yang; Weidong Qi; Zhaoxia Wang; Licheng Jiao
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Paper Abstract

Bandelet transform is an efficient image sparse representation approach which can adaptively approximate the geometrical regularity of image structures. In this paper, a multi-bandelets based method for SAR image compression is presented, which is constructed by combining multi-wavelet with Bandelet transform and geometric flow optimization. Compared with single wavelet, multi-wavelet has some advantages such as compact support, orthogonality, symmetry and smoothness, thus making finite length filtering, linear phase, correlation remove and good frequency domain characteristics possible, which are very desirable in image compression. Moreover, in our method the multi sub-bands collaborative decision algorithm for geometric flow optimization is proposed to obtain more accurate geometric flows. A number of simulations are taken on SAR images and the result shows that our method can provide a significant improvement over the multi-wavelet and the second generation Bandelet, both in visual fidelity and some objective evaluation criteria such as peak signal to noise ratio, equivalent numbers of looks and edge preservation index.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941Q (30 October 2009); doi: 10.1117/12.832427
Show Author Affiliations
Shuyuan Yang, Xidian Univ. (China)
Ministry of Education (China)
Weidong Qi, Xidian Univ. (China)
Ministry of Education (China)
Zhaoxia Wang, Xidian Univ. (China)
Ministry of Education (China)
Licheng Jiao, Xidian Univ. (China)
Ministry of Education (China)

Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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