Performance evaluation of preprocessing in color image segmentation

In this article we address the problem of performance of preprocessing before color image segmentation. The main goal of preprocessing is noise removal. Our interests are limited to nonlinear color filters working in the spatial domain. Most often comparing such filters is based on calculation of different quality factors (e.g. PSNR, NCD etc.). The main idea of this article is to use an evaluation function, coming from research on segmentation, to evaluate the performance of preprocessing. The experiments were realized using both original and noisy images corrupted by Gaussian and impulsive noise.