SAR图像压缩

Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers Pub Date : 1996-11-03 DOI:10.1109/ACSSC.1996.599066

F. A. Sakarya, S. Emek

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引用次数: 8

摘要

经典的图像压缩算法，如离散余弦变换(DCT)， Karhunen-Loeve变换(KLT)，以及使用小波滤波器的子带分解(SDWF)对于光学成像是很好的理解。然而，它们在合成孔径雷达(SAR)图像中的应用还没有得到很好的研究。本文将DCT、KLT和SDWF应用于经过适当预处理的原始SAR图像，并根据能量增益(E/sub C/)、变换编码增益(G/sub T/)和峰峰信噪比(PSNR)三个性能指标对结果进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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SAR image compression

Classical image compression algorithms such as discrete cosine transform (DCT), Karhunen-Loeve transform (KLT), and subband decomposition using wavelet filters (SDWF) are well-understood for optical imaging. However, their applications to synthetic aperture radar (SAR) images have not been well-studied. This paper applies DCT, KLT and SDWF to raw SAR images after appropriate preprocessing, and compares the results based on three performance criteria, namely energy gain (E/sub C/), transform coding gain (G/sub T/), and peak-to-peak signal-to-noise ratio (PSNR).

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Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers

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