Linear prediction in lossless compression of hyperspectral images

被引：36
|
作者：
Mielikainen, J [1 ]
Toivanen, P [1 ]
Kaarna, A [1 ]
机构：
[1] Lappeenranta Univ Technol, Dept Informat Technol, FIN-53851 Lappeenranta, Finland
来源：
OPTICAL ENGINEERING | 2003年 / 42卷 / 04期
关键词：
lossless compression; image compression; hyperspectral images; linear prediction; least-squares optimization;
D O I：
10.1117/1.1557174
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
This study proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing residuals, and entropy coding of these residuals. Our method achieved an average compression ratio of 3.23 using 13 airborne visible/infrared imaging spectrometer (AVIRIS) images. (C) 2003 Society of Photo-Optical Instrumentation Engineers.
引用
收藏
页码：1013 / 1017
页数：5
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