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 language | English |
|---|---|
| Pages (from-to) | 2918-2926 |
| Number of pages | 9 |
| Journal | Optical Engineering |
| Volume | 34 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 1995 Jan 1 |
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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 journal › Article
TY - JOUR
T1 - Fast feature-based vector quantization algorithm of image coding
AU - Lin, Yih Chuan
AU - Tai, Shen-Chuan
PY - 1995/1/1
Y1 - 1995/1/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=0029511911&partnerID=8YFLogxK
U2 - 10.1117/12.210743
DO - 10.1117/12.210743
M3 - Article
VL - 34
SP - 2918
EP - 2926
JO - Optical Engineering
JF - Optical Engineering
SN - 0091-3286
IS - 10
ER -