Faculty of Science and State Key Laboratory for Manufacturing Systems Engineering, Science and Technology Department, Xi'an Jiaotong University, Xi'an 710049, China
Copyright © 2010 Yu-Qian Yang et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
It is known that many image enhancement methods have a tradeoff between noise suppression
and edge enhancement. In this paper, we propose a new technique for image enhancement filtering and
explain it in human visual perception theory. It combines kernel regression and local homogeneity and
evaluates the restoration performance of smoothing method. First, image is filtered in kernel regression.
Then image local homogeneity computation is introduced which offers adaptive selection about further
smoothing. The overall effect of this algorithm is effective about noise reduction and edge enhancement.
Experiment results show that this algorithm has better performance in image edge enhancement, contrast
enhancement, and noise suppression.