A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface

Liu, Shuai, Pan, Zheng and Cheng, Xiaochun ORCID: https://orcid.org/0000-0003-0371-9646 (2017) A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals, 25 (04) . pp. 1740004-1. ISSN 1793-6543 (doi:10.1142/s0218348x17400047)

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Abstract

Fractal encoding method becomes an effective image compression method because of its high compression ratio and short decompressing time. But one problem of known fractal compression method is its high computational complexity and consequent long compressing time. To address this issue, in this paper, distance clustering in high dimensional sphere surface is applied to speed up the fractal compression method. Firstly, as a preprocessing strategy, an image is divided into blocks, which are mapped on high dimensional sphere surface. Secondly, a novel image matching method is presented based on distance clustering on high dimensional sphere surface. Then, the correctness and effectiveness properties of the mentioned method are analyzed. Finally, experimental results validate the positive performance gain of the method.

Item Type: Article
Additional Information: Article number = 1740004
Keywords (uncontrolled): Modelling and Simulation, Geometry and Topology, Applied Mathematics
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 27237
Notes on copyright: © The Author(s). This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original
work is properly cited
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Depositing User: Jisc Publications Router
Date Deposited: 24 Jul 2019 09:04
Last Modified: 03 Nov 2019 22:42
URI: https://eprints.mdx.ac.uk/id/eprint/27237

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