Presmoothing effects in Artificial Color image segmentation

Artificial Color is the application of Nature’s basic way of discriminating and segmenting images according to their spectra to technologically acquired images. It has proved very successful, but it produces somewhat ragged segmented images when the spectra of the target class and background are so close that some pixels are hard to distinguish even with the most powerful nonlinear discriminants. Post processing, including median filtering or mathematical morphology can improve the resultant segmented images, but they seldom solve the problem entirely. In this paper, we explore application of another technique utilized by Nature – presmoothing. The results are dramatically superior to those obtained by post smoothing. Qualitative and quantitative support for that assertion is offered.