Edge extraction using entropy operator
Computer Vision, Graphics, and Image Processing
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Deformable template models: a review
Signal Processing - Special issue on deformable models and techniques for image and signal processing
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Review: A comparative study of deformable contour methods on medical image segmentation
Image and Vision Computing
Image segmentation using a multilayer level-set approach
Computing and Visualization in Science
Active contours driven by local Gaussian distribution fitting energy
Signal Processing
Distance regularized level set evolution and its application to image segmentation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image segmentation and selective smoothing by using Mumford-Shah model
IEEE Transactions on Image Processing
Level set-based bimodal segmentation with stationary global minimum
IEEE Transactions on Image Processing
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In this paper, we present a scheme of improvement on the region-scalable fitting (RSF) model proposed by Li et al. (Minimization of region-scalable fitting energy for image segmentation, IEEE Transactions on Image Processing 17(10) (2008) 1940-1949) in terms of robustness to initialization and noise. First, the Gaussian kernel for the RSF energy is replaced with a ''mollifying'' kernel with compact support. Second, the RSF energy is redefined as a weighted energy integral, where the weight is local entropy deriving from a grey level distribution of image. The total energy functional is then incorporated into a variational level set formulation with two extra internal energy terms. The new RSF model not only handles better intensity inhomogeneity, but also allows for more flexible initialization and more robustness to noise compared to the original RSF model.