Multi-resolution level set image segmentation using wavelets

Level set methods have been used for image segmentation. Because partial deferential equations are solved to propagate a curve, level-set image segmentation has a slow convergence speed. The objective of this paper is to propose a method that increases the convergence speed. The proposed approach exploits the benefit of multi-resolutional analysis. Wavelet transform is used to decompose the image into different resolutions. The obtained results show a great improvement in terms of speed and accuracy.

[1]  Alin Achim,et al.  18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011 , 2011, ICIP.

[2]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

[3]  V. Caselles,et al.  A geometric model for active contours in image processing , 1993 .

[4]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Anthony J. Yezzi,et al.  Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification , 2001, IEEE Trans. Image Process..

[6]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[7]  Anthony J. Yezzi,et al.  A statistical approach to snakes for bimodal and trimodal imagery , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[8]  Baba C. Vemuri,et al.  Evolutionary Fronts for Topology-Independent Shape Modeling and Recoveery , 1994, ECCV.

[9]  Myoungho Lee,et al.  Wavelet-based Multi-resolution Deformation for Medical Endoscopic Image Segmentation , 2007, Journal of Medical Systems.

[10]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[11]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[12]  Hao Shan,et al.  Curvelet-based geodesic snakes for image segmentation with multiple objects , 2010, Pattern Recognit. Lett..

[13]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[14]  A. Haar Zur Theorie der orthogonalen Funktionensysteme , 1910 .

[15]  Jamshid Dehmeshki,et al.  Multiresolution active contour model applied on lung and colon images , 2004, SPIE Medical Imaging.

[16]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..