A Modified Embedded Zerotree Wavelet (MEZW) Algorithm for Image Compression
Journal of Mathematical Imaging and Vision
Performance Analysis of Generalized Zerotree Coders Varying the Maximum Zerotree Degree
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Set Partition Coding: Part I of Set Partition Coding and Image Wavelet Coding Systems
Foundations and Trends in Signal Processing
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
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Locating zerotrees in a wavelet transform allows encoding of sets of coefficients with a single symbol. It is an efficient means of coding if the overhead to identify the locations is small compared to the size of the zerotree sets on the average. It is advantageous in this regard to define classes of zerotrees according to the levels from the root until the remainder of the tree contains all zeroes. We call a tree with all zeroes except for the top k levels a degree-k zerotree. A degree-k zerotree coder is one that can encode degree-0 through degree-k zerotrees. We quantify the bit savings of a degree-k2 over a degree-k1, k2>k1, coder. Because SPIHT is a degree-2 zerotree coder and EZW a degree-0 zerotree coder, we are able to explain the superior efficiency of SPIHT. Finally, we gather statistics of degree-k zerotrees for different values of k in the bit planes of several image wavelet transforms to support our analysis of the coding performance of degree-k zerotree coders