Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering

An Improved Fractal Coding Method based on K-means Clustering

Authors
Hui Guo, Jie He
Corresponding Author
Hui Guo
Available Online October 2016.
DOI
https://doi.org/10.2991/mmme-16.2016.67How to use a DOI?
Keywords
Fractal image coding; k-means clustering; nearest neighbor search; variance method
Abstract

This paper focuses on a fast fractal coding algorithm based on k-means clustering. First of all, the variance method is employed to divide the sub-blocks into simple sub-blocks and complex sub-blocks; then, the k-means clustering algorithm is applied to classify the complex sub-blocks and father blocks, and the approach of nearest neighbor search is applied in the process of searching for matching father blocks, so as to match cor-responding sub-blocks with father blocks of the same type only within the neighboring scope. This method op-timizes the process of searching for matching blocks, thereby greatly shortening the encoding duration. Test results show that compared with the basic fractal coding algorithm, this method can increase the encoding speed by about 570 times, and lead to high quality of the reconstructed image.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-221-3
ISSN
2352-5401
DOI
https://doi.org/10.2991/mmme-16.2016.67How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hui Guo
AU  - Jie He
PY  - 2016/10
DA  - 2016/10
TI  - An Improved Fractal Coding Method based on K-means Clustering
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 294
EP  - 300
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.67
DO  - https://doi.org/10.2991/mmme-16.2016.67
ID  - Guo2016/10
ER  -