TITLE:        Entropy-constrained predictive trellis coded quantization: 
	      Application to hyperspectral image data compression
AUTHORS:      G. P. Abousleman, M. W. Marcellin, and B. R. Hunt
CONFERENCE:   International Conference on Acoustics, Speech, and Signal 
              Processing, Adelaide, Australia, April 1994.
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 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 about 
0.15 bits/pixel/band retains peak signal-to-noise ratios greater than 42 dB 
over most spectral bands.