Low bit-rate SAR image encoding using Bandelets with adaptive quadtree partition

Abstract

Synthetic aperture radar (SAR) is an imaging system which provides high-resolution images of earth surface. Nowadays there is an ever-growing interest in the SAR data compression because of the huge resources which require for storage and transmission. In this paper, we address the problem of SAR image compression and apply the multiscale Bandelet with adaptive quadtree partition to solve it. Because Bandelet can provide an efficient representation of geometric structures existed in images, the Bandelet based method can capture abundant textures in SAR images. Moreover, the multiscale Bandelet with adaptive quadtree partition can approximate any piecewise C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¿</sup> -regular functions when¿is unknown, so Bandelet can represent the hierarchy textures of SAR images efficiently. Embedded Block Coding with Optimal Truncation (EBCOT) coding algorithm is employed in our proposed method. Experimental results show that our method outperforms JPEG2000 and the second generation Bandelet (2G-Bandelet) compression methods on SAR image encoding at low bit rates.