Paper Details

[ Downloads: 1 | Abstract Viewed: 433 | Pages: 5 ]

Abstract of the Article

Note: English CIVILICA is in its Trial Period so Full Texts can not be provided! Persian users can download it here

Graphical Models and Contourlet Image Denoising

Authors:

[ Fahimeh Jamshidian Tehrani ] - School of Electrical and Computer Engineering, Shiraz University, Iran
[ Zohreh Azimifar ] -

Abstract:

Recently Conditional Random Fields (CRF), have presented to be a promising model for statistical inference in the vast literature of computer vision.CRFs are flexible to model long-range statistics by directly modelling the posterior distribution without any explicit prior model describing the observation. In this paper we propose a CRF-based method to denoise the contourlet coefficients and to examine effectiveness of this new tool in comparison with the state-of-the-art denoisers such as hidden Markov trees. Our interest is to implement denoising in the contourlet domain with respect to the coefficient correlations of inter-scale and also intra-scale, by defining a graphical structure within this domain.

Keywords:

Conditional Random Fields, Contourlet,Feature Function, Tree Structure, Denoising.