TITLE:        Wavelet coding of images using trellis coded quantization
AUTHORS:      P. Sriram and M. W. Marcellin
CONFERENCE:   1992 SPIE Conference on Visual Signal Processing, 
	      Orlando, Florida, April 1992.
ABSTRACT:
The discrete wavelet transform has recently emerged as a powerful technique 
for decomposing images into various multiresolution approximations. An 
image is decomposed into a sequence of orthogonal components, the first 
being an approximation of the original image at some ``base'' resolution. 
By the addition of successive (orthogonal) ``error'' images, approximations 
of higher resolution are obtained. Trellis coded quantization (TCQ) is known 
as an effective scheme for quantizing memoryless sources with low to moderate 
complexity. The TCQ approach to data compression has led to some of the most 
effective source codes found to date for memoryless sources. In this work, 
we investigate the use of entropy-constrained TCQ for encoding wavelet 
coefficients at different bit rates. The lowest-resolution sub-image is 
quantized using a 2-D discrete cosine transform encoder. For encoding the 
512x512, 8-bit, monochrome `Lenna' image, a PSNR of 39.78 dB is obtained at 
an average bit rate of 0.89 bits/pixel.