Multiband segmentation using morphological clustering and fusion $application to color image segmentation

In this paper we propose a novel approach for color image segmentation. Our approach is based on segmentation of subsets of bands using mathematical morphology followed by the fusion of the resulting segmentation "channels". For color images the band subsets are chosen as RG, RB and GB pairs, whose 2D histograms are processed as projections of a 3D histogram. The segmentations in 2D color spaces are obtained using the watershed algorithm. These 2D segmentations are then combined to obtain a final result using a region split-and-merge process. The CIE L*a*b* color space is used to measure the color distance. Our approach results in improved performance and can be generalized for multiband segmentation of images such as multispectral satellite images.