Journal of Shanghai University(Natural Science Edition) ›› 2011, Vol. 17 ›› Issue (1): 103-110.doi: 10.3969/j.issn.1007-2861.2011.

• Mathematics.Physics and Chemistry • Previous Articles    

Optimal Stopping for Image Smoothing Based on Kernel Density Estimation

LI Yi,WANG Yuan-di   

  1. (College of Sciences, Shanghai University, Shanghai 200444, China)
  • Received:2009-09-15 Online:2011-02-28 Published:2011-02-28

Abstract:

Optimal stopping has been an important issue in image smoothing based on partial differential equations. According to the independence of random variables and the kernel density estimation, a novel optimal stopping criterion is proposed, which can be used without knowing the noise variance. Numerical experiments show consistency between the results obtained with the proposed method and that of the mean square error (MSE) method. The criterion is applicable at various noise levels.

Key words: partial differential equation; image smoothing; correlation coefficient; kernel density estimation; optimal stopping

CLC Number: