Lossless to Lossy Dual-Tree BEZW Compression for Hyperspectral Images

This paper proposes a lossless to lossy compression scheme for hyperspectral images based on dual-tree Binary Embedded Zerotree Wavelet (BEZW) algorithm. The algorithm adapts Karhunen-Loève Transform and Discrete Wavelet Transform to achieve 3-D integer reversible hybrid transform and decorrelate s...

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Vydáno v:IEEE transactions on geoscience and remote sensing Ročník 52; číslo 9; s. 5765 - 5770
Hlavní autoři: Kai-jen Cheng, Dill, Jeffrey
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.09.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Approximation methods
Coding
Compaction
Discrete wavelet transforms
Embedded zerotree wavelet (EZW)
hyperspectral images
Hyperspectral imaging
Image coding
Image compression
Infrared imaging
Karhunen-Loève transform (KLT)
Lossless
matrix factorization
predictive coding
Set Partitioning in Hierarchical Trees (SPIHT)
Spectrometers
Three dimensional
transform-based coding
Transforms
wavelet transform
matrix factorization
Karhunen¿Loève transform (KLT)
predictive coding
Embedded zerotree wavelet (EZW)
transform-based coding
wavelet transform
Set Partitioning in Hierarchical Trees (SPIHT)
hyperspectral images
ISSN:0196-2892, 1558-0644
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Shrnutí:This paper proposes a lossless to lossy compression scheme for hyperspectral images based on dual-tree Binary Embedded Zerotree Wavelet (BEZW) algorithm. The algorithm adapts Karhunen-Loève Transform and Discrete Wavelet Transform to achieve 3-D integer reversible hybrid transform and decorrelate spectral and spatial data. Since statistics of the hyperspectral image are not symmetrical, the asymmetrical dual-tree structure is introduced. The 3-D BEZW algorithm compresses hyperspectral images by implementing progressive bitplane coding. The lossless and lossy compression performance is compared with other state-of-the-art predictive coding and transform-based coding algorithms on Airborne Visible/Infrared Imaging Spectrometer images. Results show that the 3-D-BEZW lossless compression performance is comparable with the best predictive algorithms, while its computational cost is comparable with those of transform-based algorithms.
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ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2013.2292366