Variational Methods and PDEs and Optimisation for Image Processing

Semester
Third semester: UB, Bordeaux
Credit
6
Class Type
Lecture, Practical
Type of the exam
Final Exam, Practical works
Lecturer
Pr. Jean-François Aujol
Hours per week
4

Objectives

A first objective of this class is to present variational approaches and partial differential equations in image processing. The students will learn to mathematically model image processing problems. Students are given the basis in order to be able to adapt classical variational models and PDEs to situations they might encounter in their future professional life.

A second objective of this class is to introduce some basics of optimization. Thanks to the first part of the course, the students can propose mathematically sounded criterion to minimize. They then need to be able to efficiently tackle them, which is the second objective of this course.

Practical labs will illustrate the theoretical principles developed in the course.

For more information, please download the teaching guide HERE

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