Hyperspectral image compression using entropy-constrained predictive trellis coded quantization

Glen P. Abousleman; Michael W. Marcellin; Bobby R. Hunt

doi:10.1109/83.563321

Hyperspectral image compression using entropy-constrained predictive trellis coded quantization

Glen P. Abousleman, Michael W. Marcellin, Bobby R. Hunt

Research output: Contribution to journal › Article › peer-review

53 Scopus citations

Abstract

A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands.

Original language	English (US)
Pages (from-to)	566-573
Number of pages	8
Journal	IEEE Transactions on Image Processing
Volume	6
Issue number	4
DOIs	https://doi.org/10.1109/83.563321
State	Published - 1997
Externally published	Yes

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design

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10.1109/83.563321

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title = "Hyperspectral image compression using entropy-constrained predictive trellis coded quantization",

abstract = "A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands.",

author = "Abousleman, {Glen P.} and Marcellin, {Michael W.} and Hunt, {Bobby R.}",

note = "Funding Information: Manuscript received June 22, 1994; revised September 11, 1996. This work was supported in part by the NSF under Grant NCR-9258374. Portions of this work were presented at the 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, Adelaide, Australia, April, 1994. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Rama Chellappa.",

year = "1997",

doi = "10.1109/83.563321",

language = "English (US)",

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AU - Abousleman, Glen P.

AU - Marcellin, Michael W.

AU - Hunt, Bobby R.

N1 - Funding Information: Manuscript received June 22, 1994; revised September 11, 1996. This work was supported in part by the NSF under Grant NCR-9258374. Portions of this work were presented at the 1994 IEEE International Conference on Acoustics, Speech, and Signal Processing, Adelaide, Australia, April, 1994. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Rama Chellappa.

PY - 1997

Y1 - 1997

N2 - A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands.

AB - A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands.

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Hyperspectral image compression using entropy-constrained predictive trellis coded quantization

Abstract

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