Reduced dimension Vector Quantization encoding method for image compression

Yan Wang*, Amine Bermak, Farid Boussaid

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The codebook and image block compression by Compressive Sampling (CS) in Vector Quantization (VQ) is proposed for image coding. Both the memory storage and the computational complexity in the VQ Encoder could be reduced for resources constrained applications. The deteriorated image produced by only using the first m transformed coefficients for codebook search could be restored and enhanced with a convex optimization program called l 1-norm minimization in the decoder. The computational intensive process is shifted from the encoder to the decoder. This feature allows it to be suitable for wireless sensor network applications.

Original languageEnglish
Title of host publication2011 IEEE 6th International Design and Test Workshop, IDT 2011
Pages110-113
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE 6th International Design and Test Workshop, IDT 2011 - Beirut, Lebanon
Duration: 11 Dec 201114 Dec 2011

Publication series

NameInternational Design and Test Workshop
ISSN (Print)2162-0601
ISSN (Electronic)2162-061X

Conference

Conference2011 IEEE 6th International Design and Test Workshop, IDT 2011
Country/TerritoryLebanon
CityBeirut
Period11/12/1114/12/11

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