Low-complexity bandelet for SAR image compression

Shuyuan Yang; Zhaoxia Wang; Weidong Qi; Licheng Jiao

doi:10.1117/12.833471

30 October 2009 Low-complexity bandelet for SAR image compression

Shuyuan Yang, Zhaoxia Wang, Weidong Qi, Licheng Jiao

Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 74941V (2009) https://doi.org/10.1117/12.833471
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Synthetic aperture radar (SAR) images compression is very important in reducing the burden of data storage and transmission. Finding efficient geometric representations of images is a central issue in improving the efficiency of image compression. Bandelet provides an efficient way for image representation based on geometric regularity. In the second generation Bandelet, the multiscale decomposition of image is completed by 2D wavelet transform (WT) and the obtained subbands images are squared partitioned. Then a bottom to top CART algorithm is used to prune the quadtree, and finally an exhaustive searching algorithm is used to obtain the optimal direction in each square. This process is of high complexity in time and space though it can provide an efficient representation of images than WT. Considering this, we proposed a rapid implementation of Bandelet transform based on fixed size image partition, and then applied it to SAR image compression. Experiments results show that in relative to the second generation Bandelets, our proposed method has rapid implementation and comparable performance with chinalake and abq_apt in 0.5-2.0bpp. An improvement of PSNR(Peak Signal to Noise Ratio) and the preservation of edges and texture over JPEG2000 are obtained.

Citation Download Citation

Shuyuan Yang, Zhaoxia Wang, Weidong Qi, and Licheng Jiao "Low-complexity bandelet for SAR image compression", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941V (30 October 2009); https://doi.org/10.1117/12.833471

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