A Saturation-Component Based Fuzzy Mumford-Shah Model for Color Image Segmentation (CSIAM Transactions on Applied Mathematics, 2021)
In this paper, we propose and develop a novel saturation component basedfuzzy Mumford-Shah model for color image segmentation. The main feature of thismodel is that we determine different segments by using the saturation component inhue, saturation, and value (HSV) color space instead of the original red, green and blue(RGB) color space. The proposed model is formulated for multiphase segmentation ofcolor images with the assumption that a piecewise smooth function is approximatedby the product of a piecewise constant function and a smooth function. The piecewiseconstant function and the smooth function are used to represent different segmentsand to estimate the bias field respectively in the color image. The approximation iscalculated based on the saturation component which is particularly useful to distinguish edges and capture the inherent correlation among red, green and blue channelsin color images. Experimental results are presented to demonstrate that the segmentation performance of the proposed model is much better than existing color imagesegmentation methods.