SAR image compression based on multibandelets and geometric flow optimization
Shuyuan Yang, Weidong Qi, Zhaoxia Wang, Licheng Jiao · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
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.