Reduced dimension Vector Quantization encoding method for image compression

Yan Wang, Amine Bermak, Farid Boussaid

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

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

Other

Other2011 IEEE 6th International Design and Test Workshop, IDT 2011
CountryLebanon
CityBeirut
Period11/12/1114/12/11

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ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Wang, Y., Bermak, A., & Boussaid, F. (2011). Reduced dimension Vector Quantization encoding method for image compression. In 2011 IEEE 6th International Design and Test Workshop, IDT 2011 (pp. 110-113). [6123112] https://doi.org/10.1109/IDT.2011.6123112