Subject: Subject Sylbus: Variational Methods in Image Processing - 049064 (Current)

Variational Methods in Image Processing - 049064
Credit
Points
2.0
 
Given In
Semester
a
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2       3

Determination of the grade according to progress during the semester and the submission of the final thesis


Prerequisites: Image Processing and Analysis 046200


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. T

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.Rential Equations. 3. Know Advanced Image Processing Algorithms Which Are Based on These Methods.Tial Equations. 3. Know Advanced Image Processing Algorithms Which Are Based on T


Timetable to semester 01/2017 2017/2018 Winter Semester
RoomBuildingHourdayLecturerExercise
Lecture
no.Registering
Group
504Fishbach14:30-16:30MondayAssistant Professor Gilboa GuyLecture1010


Textbooks
PublishedPublisherAuthorsBook
2006springer science business mediag.aubert and p. kornprobstmathematical problems in image processing partical differential equations and the calculus
2005society for industrial and applies mathematicst.chan and j.shenimage processing and analysis variational pde wavelet and stochastic methods
1998teubnerj.weickertanisotropic diffusion in image processing vol1

Created in 25/09/2017 Time 05:32:17