Image compression using VQ and fuzzy classified algorithm

Mu King Tsay, Jen-Fa Huan, Wei Ping Chang-Chuago

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

In this paper, Fuzzy Clustering Algorithm is used for the image Tree Structure Vector Quantization (TSVQ). First, a digital image is divided into subblocks of fixed size, which consists of 4×4 blocks of pixels. By performing 2-D Discrete Cosine Transform (DCT), we select six DCT coefficients to form the feature vector. And using Fuzzy c-means algorithm in constructing the TSVQ codebook. By doing so, the algorithm can preserve the edge of image, make good image quality, and reduce the processing time while constructing Tree Structured Codebook, and coding, decoding time.

Original languageEnglish
Pages (from-to)466-471
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume1
Publication statusPublished - 1996 Dec 1
EventProceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics - Beijing, China
Duration: 1996 Oct 141996 Oct 17

Fingerprint

Discrete cosine transforms
Vector quantization
Image compression
Fuzzy clustering
Clustering algorithms
Image quality
Decoding
Pixels
Processing

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Hardware and Architecture

Cite this

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Image compression using VQ and fuzzy classified algorithm. / Tsay, Mu King; Huan, Jen-Fa; Chang-Chuago, Wei Ping.

In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Vol. 1, 01.12.1996, p. 466-471.

Research output: Contribution to journalConference article

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