3D SOM Neighborhood Algorithm

DOI

10.2991/icca-16.2016.37How to use a DOI?

Keywords

Self-organizing maps, Three-dimensional image coding, Pattern recognition, Neighborhood algorithm

Abstract

Neighborhood algorithm is an important part of 3D SOM algorithm. We proposed three kinds of neighborhood shape and two kinds of neighborhood decay function for three-dimensional self-organizing feature maps (3D SOM) algorithm and applied them to three-dimensional image compression coding. Experimental results show that the 3D orthogonal cross neighborhood shape and exponential function algorithm have better peak signal to noise ratio (PSNR) and subject quality than others.

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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TY  - CONF
AU  - Hongsong Li
AU  - Fulin Cheng
AU  - Yanhua Wang
AU  - Xinyu Ai
PY  - 2016/01
DA  - 2016/01
TI  - 3D SOM Neighborhood Algorithm
BT  - Proceedings of the 2016 International Conference on Intelligent Control and Computer Application
PB  - Atlantis Press
SP  - 162
EP  - 164
SN  - 2352-538X
UR  - https://doi.org/10.2991/icca-16.2016.37
DO  - 10.2991/icca-16.2016.37
ID  - Li2016/01
ER  -