An Image Fusion Approach Based on Markov Random Fields
Document Type
Article
Publication Date
12-1-2011
DOI
http://dx.doi.org/10.1109/tgrs.2011.2158607
Abstract
Markov random field (MRF) models are powerful tools to model image characteristics accurately and have been successfully applied to a large number of image processing applications. This paper investigates the problem of fusion of remote sensing images, e.g., multispectral image fusion, based on MRF models and incorporates the contextual constraints via MRF models into the fusion model. Fusion algorithms under the maximum a posteriori criterion are developed to search for solutions. Our algorithm is applicable to both multiscale decomposition (MD)-based image fusion and non-MD-based image fusion. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithms.
Publication Information
Xu, Min; Chen, Hao; and Varshney, Pramod K.. (2011). "An Image Fusion Approach Based on Markov Random Fields". IEEE Transactions on Geoscience and Remote Sensing, 49(12), 5116-5127.