1 SUBBAND IMAGE COMPRESSION Aria Nosratinia1, Geoffrey Davis2, Zixiang Xiong3, and Rajesh Rajagopalan4
1 SUBBAND IMAGE COMPRESSION Aria Nosratinia1, Geo®rey Davis2, Zixiang Xiong3, and Rajesh Rajagopalan4 1Dept of Electrical and Computer Engineering, Rice University, Houston, TX 77005 2Math Department, Dartmouth College, Hanover, NH 03755 3Dept. of Electrical Engineering, University of Hawaii, Honolulu, HI 96822 4Lucent Technologies, Murray Hill, NJ 07974 Abstract: This chapter presents an overview of subband/wavelet image com- pression. Shannon showed that optimality in compression can only be achieved with Vector Quantizers (VQ). There are practical di±culties associated with VQ, however, that motivate transform coding. In particular, reverse water¯ll- ing arguments motivate subband coding. Using a simpli¯ed model of a subband coder, we explore key design issues. The role of smoothness and compact sup- port of the basis elements in compression performance are addressed. We then look at the evolution of practical subband image coders. We present the rudi- ments of three generations of subband coders, which have introduced increasing degrees of sophistication and performance in image compression: The ¯rst gen- eration attracted much attention and interest by introducing the zerotree con- cept. The second generation used adaptive space-frequency and rate-distortion optimized techniques. These ¯rst two generations focused largely on inter-band dependencies. The third generation includes exploitation of intra-band depen- dencies, utilizing trellis-coded quantization and estimation-based methods. We conclude by a summary and discussion of future trends in subband image com- pression. 1 2 1.1 INTRODUCTION Digital imaging has had an enormous impact on industrial applications and scienti¯c projects. It is no surprise that image coding has been a subject of great commercial interest.
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