### Abstract

In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.

Original language | English |
---|---|

Pages (from-to) | 1109-1116 |

Number of pages | 8 |

Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |

Volume | E82-A |

Issue number | 6 |

Publication status | Published - 1999 Jan 1 |

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### Keywords

- Fuzzy c-means algorithm
- Fuzzy clustering
- Image compression
- Image processing
- Vector quantization

### ASJC Scopus subject areas

- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics

### Cite this

**A fuzzy entropy-constrained vector quantizer design algorithm and its applications to image coding.** / Hwang, Wen Jyi; Hong, Sheng Lin.

Research output: Contribution to journal › Article

*IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences*, vol. E82-A, no. 6, pp. 1109-1116.

}

TY - JOUR

T1 - A fuzzy entropy-constrained vector quantizer design algorithm and its applications to image coding

AU - Hwang, Wen Jyi

AU - Hong, Sheng Lin

PY - 1999/1/1

Y1 - 1999/1/1

N2 - In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.

AB - In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.

KW - Fuzzy c-means algorithm

KW - Fuzzy clustering

KW - Image compression

KW - Image processing

KW - Vector quantization

UR - http://www.scopus.com/inward/record.url?scp=0032684912&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032684912&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0032684912

VL - E82-A

SP - 1109

EP - 1116

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 6

ER -