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Adaptive block truncation coding technique using edge-based quantization approach

delete2015-04-01
delete20
PRE
AI
J
Jayamol Mathews *
M
Madhu S. Nair
DOI:10.1016/j.compeleceng.2015.01.001delete
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Abstract

Abstract

En 中文
In this paper a new approach of edge-based quantization for the compression of gray scale images using an Adaptive Block Truncation Coding technique (ABTC-EQ) is proposed, to improve the compression ratio (CR) with high picture quality. Quantization is done based on the edge information contained in each block of pixels of the image. Conventional BTC method retains the visual quality of the reconstructed image but it shows some artifacts near the edges. In conventional BTC and variants, same quantization is done for all pixel values with different block sizes so that CR is static for images with a fixed block size. But in the case of proposed method since the quantization is done based on the edge information, CR become dynamic and consequently achieves better visual quality with better CR. The experimental analysis based on subjective and quantitative analysis proved that the proposed method outperforms other BTC variants. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Image compression
Lossy compression
Block truncation coding
Edge detection
k-means clustering
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Journal

C
Computers and Electrical Engineering
IF:
4.9
Papers:
6.7K
Citations:
1.3W

Organization

U
University of Kerala
Scholars:
1.7K
Papers: 1.4K
Citations: 1.5K
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