MRF and Dempster-Shafer theory for simultaneous shadow/vegetation detection on high resolution aerial color images

This paper presents a new method for simultaneously detecting shadows and vegetation in remote sensing images, based on Otsu's thresholding method and Dempster-Shafer (DS) fusion which aims at combining different shadow indices and vegetation indices in order to increase the information quality and to obtain a more reliable and accurate segmentation result. The DS fusion is carried out pixel by pixel and is incorporated in the Markovian context while obtaining the optimal segmentation with the energy minimization scheme associated with the MRF. This new approach is applied on remote sensing images and demonstrates its efficiency.