Abstract
A novel vector quantizer (VQ) design algorithm for noisy channels is presented in this paper. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, performs the codeword training using an optimal fuzzy clustering technique where the channel noise is taken into account. In the existing crisp channel-optimized VQ (CCOVQ) design algorithms, the quantization accuracy is traded for less sensitivity to channel noise. However, because of utilizing the optimal fuzzy clustering process for VQ design, the FCOVQ algorithm can effectively reduce the sensitivity to channel noise while maintaining the quantization accuracy. Therefore, given the same noisy channel, the FCOVQ can have better rate-distortion performance than that of the CCOVQ techniques.
| Original language | English |
|---|---|
| Title of host publication | Image and Multidimensional Signal ProcessingMultimedia Signal Processing |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1895-1898 |
| Number of pages | 4 |
| Volume | 4 |
| ISBN (Electronic) | 0780362934 |
| DOIs | |
| Publication status | Published - 2000 Jan 1 |
| Event | 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey Duration: 2000 Jun 5 → 2000 Jun 9 |
Other
| Other | 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 |
|---|---|
| Country | Turkey |
| City | Istanbul |
| Period | 00/6/5 → 00/6/9 |
Fingerprint
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
Fuzzy channel-optimized vector quantization for image coding. / Hwang, Wen Jyi; Lin, Chin Tsai.
Image and Multidimensional Signal ProcessingMultimedia Signal Processing. Vol. 4 Institute of Electrical and Electronics Engineers Inc., 2000. p. 1895-1898 859198.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Fuzzy channel-optimized vector quantization for image coding
AU - Hwang, Wen Jyi
AU - Lin, Chin Tsai
PY - 2000/1/1
Y1 - 2000/1/1
N2 - A novel vector quantizer (VQ) design algorithm for noisy channels is presented in this paper. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, performs the codeword training using an optimal fuzzy clustering technique where the channel noise is taken into account. In the existing crisp channel-optimized VQ (CCOVQ) design algorithms, the quantization accuracy is traded for less sensitivity to channel noise. However, because of utilizing the optimal fuzzy clustering process for VQ design, the FCOVQ algorithm can effectively reduce the sensitivity to channel noise while maintaining the quantization accuracy. Therefore, given the same noisy channel, the FCOVQ can have better rate-distortion performance than that of the CCOVQ techniques.
AB - A novel vector quantizer (VQ) design algorithm for noisy channels is presented in this paper. The algorithm, termed fuzzy channel-optimized vector quantizer (FCOVQ) design algorithm, performs the codeword training using an optimal fuzzy clustering technique where the channel noise is taken into account. In the existing crisp channel-optimized VQ (CCOVQ) design algorithms, the quantization accuracy is traded for less sensitivity to channel noise. However, because of utilizing the optimal fuzzy clustering process for VQ design, the FCOVQ algorithm can effectively reduce the sensitivity to channel noise while maintaining the quantization accuracy. Therefore, given the same noisy channel, the FCOVQ can have better rate-distortion performance than that of the CCOVQ techniques.
UR - http://www.scopus.com/inward/record.url?scp=0033708489&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0033708489&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2000.859198
DO - 10.1109/ICASSP.2000.859198
M3 - Conference contribution
AN - SCOPUS:0033708489
VL - 4
SP - 1895
EP - 1898
BT - Image and Multidimensional Signal ProcessingMultimedia Signal Processing
PB - Institute of Electrical and Electronics Engineers Inc.
ER -