A resolution adaptive video compression system

Serhan Uslubas*, Ehsan Maani, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Scopus citations

Abstract

Modern video encoding systems employ block-based,multi-mode, spatio-temporal prediction methods in order to achieve high compression efficiency. A common practice is to transform, quantize and encode the difference between the prediction and the original along with the system parameters. Obviously, it's crucial to design better prediction and residual encoding methods to obtain higher compression gains. In this work, we examine two such systems which utilize subsampled representations of the sequence and residual data. In the first system, we consider a method for reorganizing, downsampling and interpolating the residual data. In the second system, we propose a new method that employs lower resolution intensity values for spatial and motion-compensated prediction. Both of these methods are macroblock adaptive in the rate-distortion sense. Our experiments show that implementing these methods brings additional compression efficiency compared to the state-of-the-art video encoding standard H.264/AVC.

Original languageEnglish (US)
Title of host publicationIntelligent Multimedia Communication
Subtitle of host publicationTechniques and Applications
EditorsChang Wen Chen, Zhu Li, Shiguo Lian
Pages167-194
Number of pages28
DOIs
StatePublished - Mar 24 2010

Publication series

NameStudies in Computational Intelligence
Volume280
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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