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Contact

Dominique Béréziat
Head of the VCC program at SU

courriel : master.info.digit-vcc@upmc.fr

 

 

Advanced methods for image analysis

 

Person Responsible for Module (Name, Mail address):

Isabelle Bloch, Isabelle.Bloch@telecom-paris.fr

Credit Points (ECTS): 6 Module-ID: MU5IN650
University: Sorbonne Université Department: Master Informatique

Description

This course presents advanced theories of image processing and analysis. Formalisms include continuous, discrete, algebraic, analytical and statistical approaches. The course ranges from mathematical aspects to algorithms, for pre-processing, segmentation, etc. Illustrations are provided in various domains (natural images, medical images, remote sensing images...). The course includes lessons and practical work.

Prerequisites for Participation

  • Specific prerequisites: Basics in image processing and pattern recognition.
  • Recommended prerequisites: Good level in applied mathematics and computer science.
  • Programming languages: Python, Matlab

Intended Learning Outcomes

At this end of this course, the students will have advanced knowledge and skills in various theories of image processing and analysis. They will be able to solve theoretical problems, as well as applied ones.

Content

  • Mathematical morphology
  • Markov random field
  • Graph cut optimization
  • Active contours, level sets, deformable models
  • Patch-based and non-local methods
  • A contrario methods
  • Space-scales and wavelets

Assessment and Grading Procedures

  • Written examen and evaluation of pratical works
  • Examiners: Isabelle Bloch, Florence Tupin, Yann Gousseau, Dominique Béréziat

Workload calculation (contact hours, homework, exam preparation,..)

  • 4h weekly contact hours x 15 weeks = 60 h
  • 4h weekly hours preparation and afterwork x 15 weeks = 60 h
  • Exams preparation: 30 h

Recommended Reading, Course Material

  • Image Processing, H. Maître et al., 2008, London, UK, ISTE Wiley.