DocumentCode
1781377
Title
MRF and CRF Based Image Denoising and Segmentation
Author
Wei Zhang ; Min Li
Author_Institution
Sch. of Math. & Stat., Beihua Univ., Jilin, China
fYear
2014
fDate
28-30 Nov. 2014
Firstpage
128
Lastpage
131
Abstract
In this work, we employ a pair wise Markov Random Field (MRF) and a Conditional Random Field (CRF) for bi-level image segmentation and denoising. For both tasks, the Ising pair wise model and the Iterative Conditional Mode (ICM) inference method are implemented, assuming the parameters of the unary and pair wise potentials are known. Experimental results demonstrate the effectiveness of the proposed algorithm.
Keywords
Markov processes; image denoising; image segmentation; inference mechanisms; CRF; ICM inference method; Ising pairwise model; MRF; Markov random field; conditional random field; image denoising; image segmentation; iterative conditional mode; Accuracy; Computational modeling; Computer vision; Image denoising; Image segmentation; Noise; Noise reduction;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Home (ICDH), 2014 5th International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4799-4285-5
Type
conf
DOI
10.1109/ICDH.2014.32
Filename
6996747
Link To Document