1 November 2008 Hyperspectral image compression using a three-dimensional embedded zeroblock coding algorithm
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Abstract
Motion-compensated three-dimensional embedded zeroblock coding (MC 3-D EZBC) is a successful state-of-the-art video compression algorithm. We propose a hyperspectral image compression coder based on the 3-D EZBC algorithm without motion compensation. This coder adopts the 3-D wavelet transform to decorrelate and the 3-D EZBC algorithm without motion compensation to process bitplane zeroblock coding. For achieving good coding performance, the diverse 3-D wavelet transform structures and the several wavelet filters are respectively compared and evaluated on the basis of floating-point lossy compression and lossless-to-lossy compression. We also study the problems of the optimal unitary scaling factors and list initialization order. Finally, the best choices were found for a given application, via the extensive experiments and analyses. Moreover, in comparison with several state-of-the-art wavelet coding algorithms, 3-D EZBC can provide better compression performance and unsupervised classification accuracy. Experimental results show that the average lossy compression performance (in floating-point mode and integer-based mode) of our coder respectively outperforms 3-D set partitioning in hierarchical trees (SPIHT) by 1.26 dB, 3-D set-partitioned embedded block (SPECK) by 0.68 dB, symmetric-tree (AT) 3-D SPIHT by 0.39 dB, and JPEG 2000-MC by 0.25 dB at 0.1 to 3.0 bits per pixel per band, and the lossless coding performance of 3-D EZBC is about 5% to 7% better than that of 3-D SPECK, 3-D SPIHT, and AT 3-D SPIHT. So the 3-D EZBC algorithm is also a good candidate to compress hyperspectral images.
©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
Ying Hou and Guizhong Liu "Hyperspectral image compression using a three-dimensional embedded zeroblock coding algorithm," Optical Engineering 47(11), 117002 (1 November 2008). https://doi.org/10.1117/1.3006097
Published: 1 November 2008
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image compression

3D image processing

Hyperspectral imaging

Wavelet transforms

Wavelets

Algorithms

Discrete wavelet transforms

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