A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface
Article
Liu, S., Pan, Z. and Cheng, X. 2017. A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals. 25 (04), pp. 1740004-1-11. https://doi.org/10.1142/s0218348x17400047
| Type | Article |
|---|---|
| Title | A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface |
| Authors | Liu, S., Pan, Z. and Cheng, X. |
| 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. |
| Keywords | Fractal Image Compression; Sphere Surface; Distance Clustering |
| Publisher | World Scientific Publishing Co. Pte Ltd |
| Journal | Fractals |
| ISSN | 0218-348X |
| Electronic | 1793-6543 |
| Publication dates | |
| Online | 02 Jun 2017 |
| Aug 2017 | |
| Publication process dates | |
| Submitted | 05 Jan 2017 |
| Accepted | 04 Mar 2017 |
| Deposited | 24 Jul 2019 |
| Output status | Published |
| Publisher's version | License |
| Copyright Statement | © 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 |
| Digital Object Identifier (DOI) | https://doi.org/10.1142/s0218348x17400047 |
| Web of Science identifier | WOS:000406309200005 |
| Language | English |
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