Course Camera Technology Application


Responsible: Prof.Dr. Fischer

Course

Meets requirements of following modules(MID)

Course Organization

Version
created 2013-04-30
VID 2
valid from WS 2012/13
valid to
Course identifiers
Long name Camera Technology Application
CID F07_AKAT
CEID (exam identifier)

Contact hours per week (SWS)
Lecture
Exercise (unsplit)
Exercise (split)
Lab
Project 2
Seminar
Tutorial(voluntary)
Total contact hours
Lecture
Exercise (unsplit)
Exercise (split)
Lab
Project 30
Seminar
Tutorial (voluntary)
Max. capacity
Exercise (unsplit)
Exercise (split)
Lab
Project 18
Seminar

Total effort (hours): 180

Instruction language

  • German, 70 %
  • English, 30 %

Study Level

  • Undergraduate

Prerequisites

  • none

Textbooks, Recommended Reading

  • E.A. Weber, Foto Praktikum, Birkhäuser
  • A. J. Theuwissen, Solid-State Imaging with Charge-Coupled Devices, Kluwer 1995
  • G. R. Hopkinson, T. M. Goodman, S. R. Prince, A Guide to the Use and Calibration of Detector Array Equipment, SPIE 2004
  • G. C. Holst, T. S. Lomheim, CMOS/CCD Sensors and Camera Systems, SPIE
  • J. Nakamura, Image Sensors and Signal Processing for Digital Still Cameras, Taylor & Francis
  • Reinhard/Ward/Pattanaik/Debevec, High Dynamic Range Imaging, Elsevier 2010

Instructors

  • Prof. Dr. Gregor Fischer
  • Prof. Dr. Dirk Poggemann

Supporting Scientific Staff

  • tba

Transcipt Entry

Camera Technology Application

Assessment

Type
wE normal case (except on small numbers of assessments: oE)

Total effort [hours]
wE 10

Frequency: 1/Jahr


Course components

Project

Objectives

Contents
  • multiple image methods
    • HDR (still picture and video)
    • image stacking (focus bracketing) -> 3D, depth of field extension
    • panorama stitching
    • 3D-imaging
  • test proceedures
    • OECF, SNR, MTF, color reproduction
    • investigation and comparison of quality
  • processing methods
    • raw data conversion
    • HDR-tonemapping
    • noise suppression and dynamic optimization
  • industrial imaging applications
    • surface inspection metallic/nonmetallic (bright field/dark field, polarization, raw image processing)
    • optical measurement (measurement of distribution of luminous intensity with a camera, BRDF measurement, ...)
    • thermography with IR-camera
    • surveillance cameras

Acquired Skills
  • designing and modelling of a procedure in a digital camera
  • balancing chances and risks for different problem-solving approaches
  • comprehend and understand scientific texts in English
  • presentation of project results in English

Operational Competences
  • solve a problem by application of knowledges and skills from image sensor- and camera technology
  • determination of basic requirements on interface, hardware and software for a specific problem
  • inquireries on scientific publications in the field of image sensor- and camera technology
    • feasibility-check of common procedures to solve problems from the task definition
    • implementation of procedures in own programs
    • combination of procedures in own programs
  • accomplish project task in a team
    • plan and manage projects
    • stick to agreements and deadlines
    • achieve a solution in a team
    • plan and execute reviews

Additional Component Assessment

Type
fAP 2-3 eTests, 20min each (each 1x repeatable)
fPS supervised problem solving

Contribution to course grade
fAP assessed problem solving
fPS not rated

Frequency: 1/Jahr

Topic-Revision: r3 - 11 Jan 2016, GeneratedContent
 
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