1 July 1999 Activity driven nonlinear diffusion for color image watershed segmentation
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Abstract
Nonlinear diffusion processes and watershed algorithms have been well studied for gray-scale image segmentation. In this paper we extend the use of these techniques to color or multichannel images. First, we formulate a general definition for a nonlinear diffusion process using the concept of an activity image that can be calculated for several image components. Then, we explain how the final activity image, obtained as a result of the nonlinear diffusion process, is fed through a watershed algorithm, yielding the segmentation of the image. The qualitative performance of the algorithm is illustrated with results for both gray-scale and color photographic images. Finally, we discuss the segmentation results obtained using a few well-known color spaces and demonstrate that a color principal component analysis gives the best results.
Patrick De Smet, Rui Luis V. P. M. Pires, Danny De Vleeschauwer, Ignace Bruyland, "Activity driven nonlinear diffusion for color image watershed segmentation," Journal of Electronic Imaging 8(3), (1 July 1999). https://doi.org/10.1117/1.482676
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