|
|
Compression of SAR Image Based on Spatial-OrientationTree in Wavelet Domain |
ZHAO Yue-dong1,2, YANG Ru-liang2 |
(1.Graduate School,Chinese Academy of Sciences,Beiijng100039,China;2.Institute of Electronics,Chinese Academy of Sciences,Beijing100080,China) |
|
|
Abstract The synthetic aperture radar (SAR) is an airborne or spaceborne radar mapping technique for gener-ating high-resolution maps of surface target areas and terrain. Its images usually have big size and contain alarge amount of data. So it is a key problem in SAR image data processing that how to compress the image toreduce data amount effectively so that it can be saved or transmitted conveniently. In recent years, wavelettransform is widely used in the field of image compression. The Spatial-Orientation Tree (SOT) Structure playsa very important role in compression of SAR image based on Wavelet transform. Both the Embedded Zero-treeWavelet (EZW) and the Set Partitioning in Hierarchical Trees (SPIHT) coding schemes utilize the parent-chil-dren relationship in SOT. EZW is a simple, yet remarkably effective, image compression algorithm, have theproperty that bits in the bit stream are generated in order of importance, yielding a fully embedded code. SARimage suffer from speckle noise that seriously degrades image quality and compressibility. Removal of specklenoise can enhance correlations of pixels and compressibility of SAR image. As a very efficient structure to inves-tigate the spatial correlations among wavelet coefficients at different resolutions, SOT has not been well used innoise removal.In this paper we proposed a SOT structure based method, which integrated speckle noise removal andEZW algorithm. Results of compression of large numbers of Airborne SAR images validate the proposedmethod is efficient and better than JPEG and EZW algorithm.
|
Received: 23 April 2004
Published: 26 December 2011
|
|
〔1〕 张澄波.综合孔径雷达:原理、系统分析与应用〔M〕.北京:科学出版社,1989.〔2〕 Mallat S. Multifrequency Channel Decomposition of Images and Wavelet Models〔J〕. IEEE Trans on ASSP, 1989, 37(12):2091-2110.〔3〕 Jerine M. Embedded Image Coding Using Zerotrees of Wavelet Coefficients〔J〕. IEEE Trans on Signal Processing, 1993,41(12):3445-3462.〔4〕 Amir S, William A. Pearlman, A New, Fast and Efficient Im-age Codec Based Set Partitioning in Hierarchical Trees〔J〕. IEEETrans on Circuits and Systems for Video Technology, 1996,6(3):243-250.〔5〕 Seisuke F, Haruto H. Smoothing Effect of Wavelet-Based Sp- eckle Filtering The Haar Basis case〔J〕. IEEE Trans Geosci Re-mote Sensing, 1999,37:1168-1172.〔6〕 Donoho D. De-noising by Soft-thresholding〔J〕. IEEE Trans onInformation Theory, 1995,41:613-627.〔7〕 Cheng Peng, Andrew Chan. Speckle Noise Removal in SAR Im-age Based on SOT Structure in Wavelet Domain〔J〕. Geoscienceand Remote Sensing Symposium, 2001,7:3039-3041. |
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|