TITLE:        Image coding using wavelet transforms and entropy-constrained
	      trellis coded quantization
AUTHORS:      P. Sriram and M. W. Marcellin
CONFERENCE:   International Conference on Acoustics, Speech, and Signal
              Processing, Minneapolis, Minnesota, April 1993
ABSTRACT:
The discrete wavelet transform has recently emerged as a powerful 
technique for decomposing images into various multi-resolution 
approximations. Multi-resolution decomposition schemes have proven to 
be very effective for high-quality, low bit-rate image coding. In this 
work, we investigate the use of entropy-constrained trellis coded 
quantization for encoding the wavelet coefficients of both monochrome 
and color images.  Excellent peak signal-to-noise ratios are obtained 
for encoding monochrome and color versions of the 512x512 ``Lenna'' image. 
Comparisons with other results from the literature reveal that the 
proposed wavelet coder is quite competitive.