Prediction trees and lossless image compression

Nasir D. Memon, Spyros S. Magliveras, Khalid Sayood

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Prediction techniques have been applied very successfully in compression of speech data. Similar success with image data has not been obtained. In this paper we employ an approach based on spanning trees to construct non-linear predictive schemes. This approach holds promise in leading to new simple and effective non-linear predictive schemes. Our approach is novel in the sense that images are not scanned in any predetermined fashion nor is the prediction for any pixel based on a single fixed scheme. Preliminary implementations give promising results over a wide range of images.

Original languageEnglish (US)
Title of host publicationData Compression Conference 1991
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)0818692022
StatePublished - 1991
Event1991 Data Compression Conference, DCC 1991 - Snowbird, United States
Duration: Apr 8 1991Apr 11 1991

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Conference1991 Data Compression Conference, DCC 1991
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Networks and Communications


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