Fast feature-based vector quantization algorithm of image coding

Yih Chuan Lin, Shen-Chuan Tai

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A fast vector quantization algorithm is presented that exploits the spatial redundancy between neighboring vectors of pixels in an image to improve the performance of the triangle inequality elimination ruler, and employs the integral projection technique, a dimension-reduction method, to reduce the computational complexity of calculating distortion measure. Application of dimension reduction in distortion measures may result in some degradation of objective image quality. But a significant complexity reduction of over 90% in comparison with the conventional full-search method can be achieved. The degradation of image quality is only less than 0.2 dB in peak signal-to-noise ratio. Acceptable image quality should be obtained successfully.

Original languageEnglish
Pages (from-to)2918-2926
Number of pages9
JournalOptical Engineering
Volume34
Issue number10
DOIs
Publication statusPublished - 1995 Jan 1

Fingerprint

vector quantization
Vector quantization
Image coding
Image quality
coding
Degradation
degradation
Redundancy
Computational complexity
Signal to noise ratio
redundancy
Pixels
triangles
elimination
signal to noise ratios
projection
pixels

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

Cite this

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Fast feature-based vector quantization algorithm of image coding. / Lin, Yih Chuan; Tai, Shen-Chuan.

In: Optical Engineering, Vol. 34, No. 10, 01.01.1995, p. 2918-2926.

Research output: Contribution to journalArticle

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