Title :
MRF and CRF Based Image Denoising and Segmentation
Author :
Wei Zhang ; Min Li
Author_Institution :
Sch. of Math. & Stat., Beihua Univ., Jilin, China
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;
Conference_Titel :
Digital Home (ICDH), 2014 5th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-4285-5
DOI :
10.1109/ICDH.2014.32
