Student's Portal

Basic Principles in Energy Minimization Methods (convex and Non Convex Nonlinear Diffusion (perona Malik) and Anisotropic Diffusion (weickert). Contour Evolutions Using Level Sets, Active Contour Segmentation. Numerical Implementation Of Nonlinear Pde's. Total Variation Denoising, Denoising With Higher Order Functionals. Evolution of Manifolds. Nonlocal Operators and Energies. Applications Denoising,deconvolution, Image Enhancement, Segmentation, Optical Flow, Image Registration. Learning Outcomes# at The End of The Course The Student Will# 1. Be Able to Use Mathematical Knowledge and Will Be Familiar With Convex Optimization Tools. 2. Be Able to Implement Code For Numerical Solution of Nonlinear Partial Differential Equations. 3. Know Advanced Image Processing Algorithms Which Are Based On These Methods.

Faculty: Electrical and Computer Engineering
|Graduate Studies

Pre-required courses

46200 - Image Processing and Analysis