Zerotree Design for Image Compression: Toward Weighted Universal Zerotree Coding

We consider the problem of optimal, data-dependent zerotree design for use in weighted universal zerotree codes for image compression. A weighted universal zerotree code (WUZC) is a data compression system that replaces the single, data-independent zerotree of Said and Pearlman with an optimal collection of zerotrees for good image coding performance across a wide variety of possible sources. We briefly describe the weighted universal zerotree encoding and design algorithms but focus primarily on the problem of optimal, data-dependent zerotree design. We demonstrate the pe$ormance of the proposed algorithm by comparing, at a variety of target rates, the pe~ormance of a Said-Pearlman style code using the standard zerotree to the pe$ormance of the same code using a zerotree designed with our algorithm. The comparison is made without entropy coding. The proposed zerotree design algorithm achieves, on a collection of combined text and grayscale images, up to 4 dB performance improvement over a Said-Pearlman zerotree.