Isorange Pairwise Orthogonal Transform

被引:8
作者
Blanes, Ian [1 ]
Hernandez-Cabronero, Miguel [1 ]
Auli-Llinas, Francesc [1 ]
Serra-Sagrista, Joan [1 ]
Marcellin, Michael W. [2 ]
机构
[1] Univ Autonoma Barcelona, Dept Informat & Commun Engn, E-08193 Barcelona, Spain
[2] Univ Arizona, Tucson, AZ 85721 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2015年 / 53卷 / 06期
关键词
Limited dynamic range expansion; onboard multi- and hyperspectral image coding; pairwise orthogonal transform (POT); progressive lossy-to-lossless; NEAR-LOSSLESS COMPRESSION;
D O I
10.1109/TGRS.2014.2374473
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Spectral transforms are tools commonly employed in multi- and hyperspectral data compression to decorrelate images in the spectral domain. The pairwise orthogonal transform (POT) is one such transform that has been specifically devised for resource-constrained contexts similar to those found on board satellites or airborne sensors. Combining the POT with a 2-D coder yields an efficient compressor for multi-and hyperspectral data. However, a drawback of the original POT is that its dynamic range expansion, i.e., the increase in bit depth of transformed images, is not constant, which may cause problems with hardware implementations. Additionally, the dynamic range expansion is often too large to be compatible with the current 2-D standard CCSDS 122.0-B-1. This paper introduces the isorange POT, a derived transform that has a small and limited dynamic range expansion, compatible with CCSDS 122.0-B-1 in almost all scenarios. Experimental results suggest that the proposed transform achieves lossy coding performance close to that of the original transform. For lossless coding, the original POT and the proposed isorange POT achieve virtually the same performance.
引用
收藏
页码:3361 / 3372
页数:12
相关论文
共 36 条
[1]   Crisp and fuzzy adaptive spectral predictions for lossless and near-lossless compression of hyperspectral imagery [J].
Aiazzi, Bruno ;
Alparone, Luciano ;
Baronti, Stefano ;
Lastri, Cinzia .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2007, 4 (04) :532-536
[2]   Performance impact of parameter tuning on the CCSDS-123 lossless multi- and hyperspectral image compression standard [J].
Auge, Estanislau ;
Enrique Sanchez, Jose ;
Kiely, Aaron ;
Blanes, Ian ;
Serra-Sagrista, Joan .
JOURNAL OF APPLIED REMOTE SENSING, 2013, 7
[3]   On optimal transforms in lossy compression of multicomponent images with JPEG2000 [J].
Bita, Isidore Paul Akam ;
Barret, Michel ;
Pham, Dinh-Tuan .
SIGNAL PROCESSING, 2010, 90 (03) :759-773
[4]   On optimal orthogonal transforms at high bit-rates using only second order statistics in multicomponent image coding with JPEG2000 [J].
Bita, Isidore Paul Akam ;
Barret, Michel ;
Pham, Dinh-Tuan .
SIGNAL PROCESSING, 2010, 90 (03) :753-758
[5]   Divide-and-Conquer Strategies for Hyperspectral Image Processing A review of their benefits and advantages [J].
Blanes, Ian ;
Serra-Sagrista, Joan ;
Marcellin, Michael W. ;
Bartrina-Rapesta, Joan .
IEEE SIGNAL PROCESSING MAGAZINE, 2012, 29 (03) :71-81
[6]   Pairwise Orthogonal Transform for Spectral Image Coding [J].
Blanes, Ian ;
Serra-Sagrista, Joan .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (03) :961-972
[7]   Cost and Scalability Improvements to the Karhunen-Loeve Transform for Remote-Sensing Image Coding [J].
Blanes, Ian ;
Serra-Sagrista, Joan .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (07) :2854-2863
[8]  
BRUEKERS FAML, 1992, IEEE J SEL AREA COMM, V10, P130
[9]   BIORTHOGONAL BASES OF COMPACTLY SUPPORTED WAVELETS [J].
COHEN, A ;
DAUBECHIES, I ;
FEAUVEAU, JC .
COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS, 1992, 45 (05) :485-560
[10]  
Consultative Committee for Space Data Systems (CCSDS), 2005, BLUE BOOK