Multi-Polarimetric SAR Image Compression Based on Three Dimensional Matrix Transform

ZHANG Wen-chao; WANG Yan-fei; PAN Zhi-gang

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Multi-Polarimetric SAR Image Compression Based on Three Dimensional Matrix Transform

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- Multi-Polarimetric SAR Image Compression Based on Three Dimensional Matrix Transform
- Acta Electronica Sinica Vol. 35, Issue 12, Pages: 2430-2434(2007)
- 作者机构：
  
  1. 中国科学院电子学研究所,北京,100080
  2. 中国科学院研究生院,北京,100039
  3. 中国科学院电子学研究所北京,100080
  4. 中国科学院研究生院北京,100039
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN919.81
- Published：2007
- 稿件说明：
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ZHANG Wen-chao, WANG Yan-fei, PAN Zhi-gang. Multi-Polarimetric SAR Image Compression Based on Three Dimensional Matrix Transform[J]. Acta Electronica Sinica, 2007, 35(12): 2430-2434.
DOI：

ZHANG Wen-chao, WANG Yan-fei, PAN Zhi-gang. Multi-Polarimetric SAR Image Compression Based on Three Dimensional Matrix Transform[J]. Acta Electronica Sinica, 2007, 35(12): 2430-2434. DOI：

摘要

本文针对多极化合成孔径雷达(SAR)图像在极化通道之间的相关性

提出了基于三维矩阵变换的压缩方法.将多极化SAR图像(HH

VV图像)作为一个整体

进行三维矩阵变换.首先在极化通道之间进行一维DCT变换

极化平面内进行二维离散小波变换

然后对三个混合系数平面根据率失真准则分配不同比特数

采用分级树的集合划分(SPIHT)算法进行编码.由于不是单独处理每一极化图像

因此不仅可以去除各极化图像内部之间的相关性

也可以去除极化通道之间的相关性.理论推导和实验结果都表明该方法对多极化SAR图像压缩是十分有效的.

Abstract

This paper proposes a method for multi-polarimetric synthetic aperture radar (SAR) image compression based on three-dimensional matrix transform according to the correlation between the polarimetric channels.The multi-polarimetric SAR images (HH

VV) are considered as a three dimensional unit

and then are processed by three dimensional matrix transform including.One-Dimensional DCT transform among the polarimetric channels and Two-dimensional DWT transform in the polarimetric SAR image.The three mixed coefficient planes are allocated different bits according to the Rate-Distortion(R-D) criteria and encoded by SPIHT algorithm.This method doesn’t process every channel image separately

so it removes the correlation of the image inside and the correlation between the polarimetric channels.Both the theory and the experimental results show that the method in this paper is efficient for multi-polarimetric SAR image compression.

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