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Entropy-constrained predictive trellis coded quantization: application to hyperspectral image compression

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3 Author(s)
Abousleman, G.P. ; Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA ; Marcellin, M.W. ; Hunt, B.R.

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 MSE performance of an 8-state ECPTCQ system exceeds that of entropy-constrained DPCM by up to 1.0 dB. In addition, a hyperspectral image compression system is developed which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.15 bits/pixel/band retains peak signal-to-noise ratios greater than 42 dB over most spectral bands

Published in:

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on  (Volume:v )

Date of Conference:

19-22 Apr 1994