Brick-wall structured segmentation for interpolative vector quantization of images

W. F. Lee; P. C. Yuen; C. K. Chan

doi:10.1016/0923-5965(95)00032-1

Brick-wall structured segmentation for interpolative vector quantization of images

W. F. Lee^*, P. C. Yuen, C. K. Chan

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Journal article › peer-review

Abstract

A new variable block size image segmentation scheme based on the modified split- and-merge (MSM) algorithm is devised in this paper. It is shown that the position of the sampling points obtained from the MSM algorithm are located at the edge boundaries and the distance between two consecutive sampling points indicates the local activity between them. An image is partitioned using the properties of the selected sampling points. The proposed method is applied for coding of monochrome image using interpolative vector quantization (IVQ) technique. Simulation results show that the proposed method can achieve 0.8 dB PSNR improvement at a bit rate lower than the fixed block size scheme. Besides, perfect reconstruction of edges is resulted and hence excellent reconstructed image visual quality is obtained.

Original language	English
Pages (from-to)	45-54
Number of pages	10
Journal	Signal Processing: Image Communication
Volume	8
Issue number	1
DOIs	https://doi.org/10.1016/0923-5965(95)00032-1
Publication status	Published - Jan 1996

Scopus Subject Areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1016/0923-5965(95)00032-1

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title = "Brick-wall structured segmentation for interpolative vector quantization of images",

abstract = "A new variable block size image segmentation scheme based on the modified split- and-merge (MSM) algorithm is devised in this paper. It is shown that the position of the sampling points obtained from the MSM algorithm are located at the edge boundaries and the distance between two consecutive sampling points indicates the local activity between them. An image is partitioned using the properties of the selected sampling points. The proposed method is applied for coding of monochrome image using interpolative vector quantization (IVQ) technique. Simulation results show that the proposed method can achieve 0.8 dB PSNR improvement at a bit rate lower than the fixed block size scheme. Besides, perfect reconstruction of edges is resulted and hence excellent reconstructed image visual quality is obtained.",

author = "Lee, {W. F.} and Yuen, {P. C.} and Chan, {C. K.}",

year = "1996",

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T1 - Brick-wall structured segmentation for interpolative vector quantization of images

AU - Lee, W. F.

AU - Yuen, P. C.

AU - Chan, C. K.

PY - 1996/1

Y1 - 1996/1

N2 - A new variable block size image segmentation scheme based on the modified split- and-merge (MSM) algorithm is devised in this paper. It is shown that the position of the sampling points obtained from the MSM algorithm are located at the edge boundaries and the distance between two consecutive sampling points indicates the local activity between them. An image is partitioned using the properties of the selected sampling points. The proposed method is applied for coding of monochrome image using interpolative vector quantization (IVQ) technique. Simulation results show that the proposed method can achieve 0.8 dB PSNR improvement at a bit rate lower than the fixed block size scheme. Besides, perfect reconstruction of edges is resulted and hence excellent reconstructed image visual quality is obtained.

AB - A new variable block size image segmentation scheme based on the modified split- and-merge (MSM) algorithm is devised in this paper. It is shown that the position of the sampling points obtained from the MSM algorithm are located at the edge boundaries and the distance between two consecutive sampling points indicates the local activity between them. An image is partitioned using the properties of the selected sampling points. The proposed method is applied for coding of monochrome image using interpolative vector quantization (IVQ) technique. Simulation results show that the proposed method can achieve 0.8 dB PSNR improvement at a bit rate lower than the fixed block size scheme. Besides, perfect reconstruction of edges is resulted and hence excellent reconstructed image visual quality is obtained.

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DO - 10.1016/0923-5965(95)00032-1

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JO - Signal Processing: Image Communication

JF - Signal Processing: Image Communication

IS - 1

ER -

Brick-wall structured segmentation for interpolative vector quantization of images

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