This research addresses practical and theoretical issues encountered in the lossy compression of information. The problem of successive refinement, or progressive transmission, concerns efficient approaches to incremental specification of data produced by an information source in order to render it in more detail at each of several encoding stages. A prime theoretical issue is the determination of conditions under which this can be done in such a way the total data rate required is no less than that needed by someone tasked with only the final rendering in the sequence without the requirement of generating the intermediate versions. Practical algorithms inspired by theoretical advances in universal lossless data compression, especially the Lempe-Ziv and arithmetic coding formalisms, have profoundly affected the way text and data files are compressed for transmission and storage. Analogous theoretical issues and practical techniques are sought for universal lossy data compression based on searching the imprecisely described past for an approximate rather than an exact match of the next segment of the yet-to-be-encoded data. the results should significantly impact the way actual data sources, especially images and video, get encoded in practice.
