摘要
空间树结构SOT(Spatial-OrientationTree)在基于小波的SAR图像压缩中扮演着及其重要的角色,包括EZW(EmbeddedZero-treeWavelet)和SPIHT(SetPartitioninginHierarchicalTrees)的图像压缩编码方法,都利用了SOT中的父子关系。斑点噪声的存在,严重降低了SAR图像的质量和可压缩性。作为研究不同分辨率小波系数的空间相关性的非常有效的数据结构,SOT在斑点噪声去除中并没有得到很好的利用。提出一种新的SAR图像压缩方法,该方法结合基于SOT结构的斑点噪声去除和EZW嵌入式零树编码算法,对机载合成孔径雷达图像压缩实验的结果显示,该方法优于JPEG和标准EZW算法。
The synthetic aperture radar (SAR) is an airborne or spaceborne radar mapping technique for generating high-resolution maps of surface target areas and terrain. Its images usually have big size and contain a large amount of data. So it is a key problem in SAR image data processing that how to compress the image to reduce data amount effectively so that it can be saved or transmitted conveniently. In recent years, wavelet transform is widely used in the field of image compression. The Spatial-Orientation Tree (SOT) Structure plays a very important role in compression of SAR image based on Wavelet transform. Both the Embedded Zero-tree Wavelet (EZW) and the Set Partitioning in Hierarchical Trees (SPIHT) coding schemes utilize the parent-children relationship in SOT. EZW is a simple, yet remarkably effective, image compression algorithm, have the property that bits in the bit stream are generated in order of importance, yielding a fully embedded code. SAR image suffer from speckle noise that seriously degrades image quality and compressibility. Removal of speckle noise can enhance correlations of pixels and compressibility of SAR image. As a very efficient structure to investigate the spatial correlations among wavelet coefficients at different resolutions, SOT has not been well used in noise removal. \;In this paper we proposed a SOT structure based method, which integrated speckle noise removal and EZW algorithm. Results of compression of large numbers of Airborne SAR images validate the proposed method is efficient and better than JPEG and EZW algorithm.
出处
《遥感技术与应用》
CSCD
2004年第6期503-507,共5页
Remote Sensing Technology and Application
关键词
合成孔径雷达
小波变换
图像压缩
SOT
EZW
Synthetic aperture rader, Wavelet transform, Image compression, Spatial-orientation tree(SOT), Embedded zero-tree wavelet(EZW)
