Efficient Multiresolution Level Set Image Segmentation with Multiple Regions

This study is to investigate a new representation of a partition of an image domain into a fixed but arbitrary number of regions via active contours and level sets. The proposed algorithm is composed of simple closed evolving planar curves by an explicit correspondence to minimize the energy functional containing three terms: multiregion fitting energy, regularization related to the length of the curve, and the distance regularizing term to penalize the deviation of the level set function from a signed distance function. This formulation leads to a system of coupled curve evolution equations, which is easily amenable to a level set implementation, and an unambiguous segmentation because the evolving regions form a partition of the image domain at all times during curve evolution. In order to increase the robustness of the method to noise and to reduce the computational cost, a multiresolution level set schema is proposed, which can perform the evolution curves of the partitioned image at a different resolution. Given these advantages, the proposed method can get good performance and experiments show promising segmentation results on both synthetic and real images. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI:10.1117/1.3582863]