Adaptive Algorithm in Image Denoising Based on Data Mining
Authors
Corresponding Author
Yan-hua Ma
Available Online December 2008.
- DOI
- 10.2991/jcis.2008.37How to use a DOI?
- Keywords
- Data mining, Image denoising, Pepper-and-Salt Noise, Noisy density, Adaptive filtering
- Abstract
An adaptive filtering algorithm based on data mining is proposed for image de-noising when an image is merged by pep-per-and-salt noise. It can adjust the rotat-ing mask size based on the noisy density in the input image so that it raises greatly the computing speed; On the other hand, the algorithm can determine the mask co-efficients based on the noise case so that it reduces largely the error rat; And then it is more effective than other methods when the image has a higher noisy den-sity. Experimental results indicate that the adaptive filtering is superior.
- Copyright
- © 2008, 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 - Yan-hua Ma AU - Chuan-jun Liu PY - 2008/12 DA - 2008/12 TI - Adaptive Algorithm in Image Denoising Based on Data Mining BT - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008) PB - Atlantis Press SP - 215 EP - 220 SN - 1951-6851 UR - https://doi.org/10.2991/jcis.2008.37 DO - 10.2991/jcis.2008.37 ID - Ma2008/12 ER -