Lossless Hyperspectral Image Compression Using Wavelet Transform Based Spectral Decorrelation

被引：0
|
作者：
Toreyin, Behcet Ugur [1 ,2 ]
Yilmaz, Ozan [2 ]
Mert, Yakup Murat [3 ]
Turk, Fethi [2 ]
机构：
[1] Cankaya Univ, EE Muh Bol, TR-06790 Ankara, Turkey
[2] TUBITAK UZAY, TR-06531 Ankara, Turkey
[3] TUBITAK ILTAREN, TR-06800 Ankara, Turkey
来源：
2015 7TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SPACE TECHNOLOGIES (RAST) | 2015年
关键词：
hyperspectral imagery; lossless compression; integer-coefficient wavelet transforms; hyperspectral data compression; AVIRIS images; spectral decorrelation; on-board compression schemes; JPEG-LS;
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
Integer-coefficient Discrete Wavelet Transformation (DWT) filters widely used in the literature are implemented and investigated as spectral decorrelator. As the performance of spectral decorrelation step has direct impact on the compression ratio (CR), it is important to employ the most convenient spectral decorrelator in terms of computational complexity and CR. Tests using AVIRIS image data set are carried out and CRs corresponding to various subband decomposition levels are presented within a lossless hyperspectral compression framework. Two-dimensional images corresponding to each band is compressed using JPEG-LS algorithm. Results suggest that Cohen-Daubechies-Feauveau (CDF) 9/7 integer-coefficient wavelet transform with five levels of spectral subband decomposition would be an efficient spectral decorrelator for on-board lossless hyperspectral image compression.
引用
收藏
页码：250 / 253
页数：4
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