Course Image Processing

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Responsible: Prof. Dr. rer. nat. Dietmar Kunz

Course

Meets requirements of following modules(MID)

• in active programs
  • Ba MT2012 BV1

Course Organization

Version created 2011-11_09 VID 1 valid from WS 2012/13 valid to

Course identifiers Long name Image Processing CID F07_BV1 CEID (exam identifier)

Contact hours per week (SWS) Lecture 3 Exercise (unsplit) Exercise (split) Lab 2 Project Seminar Tutorial(voluntary)

Total contact hours Lecture 45 Exercise (unsplit) Exercise (split) Lab 30 Project Seminar Tutorial (voluntary)

Max. capacity Exercise (unsplit) Exercise (split) Lab 18 Project Seminar

Total effort (hours): 180

Instruction language

• German

Study Level

• Undergraduate

Prerequisites

• Basic course mathematics
• Basic course compuer science
• Basic course signal theory

Textbooks, Recommended Reading

• Burger/Burge: Digitale Bildverarbeitung
• Tönnies: Grundlagen der Bildverarbeitung

Instructors

• Prof. Dr. rer. nat. Dietmar Kunz

Supporting Scientific Staff

• tba

Transcipt Entry

Image Processing

Assessment

Type
oE	rated

Total effort [hours]
oE	10

Frequency: 2/year

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Course components

Lecture/Exercise

Objectives

Contents

• Image processing
  • camera calibration
  • homogeneous point operations
  • linear filters
  • processing in frequency domain
  • filter banks and wavelets
  • image compression
  • adaptive filters
  • change of sampling grid
  • change of quantization
  • morphological filters
  • color image processing
  • motion
  • correspondence analysis
  • registration

Operational Competences

• select problem specific image processing methods

Additional Component Assessment

• none

Lab

Objectives

Contents

• Image processing
  • camera calibration
  • homogeneous point operations
  • linear filters
  • processing in frequency domain
  • filter banks and wavelets
  • image compression
  • adaptive filters
  • change of sampling grid
  • change of quantization
  • morphological filters
  • color image processing
  • motion
  • correspondence analysis
  • registration
• Image processing with ImageJ
  • ImageJ
  • Java
  • Eclipse

Acquired Skills

• implement image processing methods
  • Plugins
  • Macros
• apply image processing methods using ImageJ

Operational Competences

• Identify and assess efects of processing in images

Additional Component Assessment

Type
fPS	solve image processing problems and present results

Contribution to course grade
fPS	prerequisite to course exam

Frequency: 1/year