Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A level set approach for computing solutions to incompressible two-phase flow
Journal of Computational Physics
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast level set method for propagating interfaces
Journal of Computational Physics
International Journal of Computer Vision
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
A PDE-based fast local level set method
Journal of Computational Physics
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear Projection Recovery in Digital Inpainting for Color Image Restoration
Journal of Mathematical Imaging and Vision
Color Image Segmentation for Objects of Interest with Modified Geodesic Active Contour Method
Journal of Mathematical Imaging and Vision
Shock filter coupled to curvature diffusion for image denoising and sharpening
Image and Vision Computing
A Two-Phase Segmentation of Cell Nuclei Using Fast Level Set-Like Algorithms
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Variational B-spline level-set: a linear filtering approach for fast deformable model evolution
IEEE Transactions on Image Processing
Updating preconditioners for nonlinear deblurring and denoising image restoration
Applied Numerical Mathematics
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Implicit active contour models are widely used in image processing and computer vision tasks. Most implementations, however, are based on explicit updating schemes and are therefore of limited computational efficiency. In this paper, we present fast algorithms based on the semi-implicit additive operator splitting (AOS) scheme for both the geometric and the geodesic active contour model. Our experimental results with synthetic and real-world images demonstrate that one can gain a speed up by one order of magnitude compared to the widely used explicit time discretization.