Course detail

Computational Photography

FIT-VYFAcad. year: 2017/2018

Current digital cameras almost completely surpass traditional photography. They do not only capture light, they in fact compute
pictures. That said, there is practically no image that would not be
computationally processed to some extent today. Visual computing is
ubiquitous. Unfortunately, images taken by amateur photographers often
lack the qualities of professional photos and some image editing is
necessary. Computational photography (CP) develops methods to enhance or extend the capabilities of the current digital imaging chain.

Learning outcomes of the course unit

Item has no knowledges.

Prerequisites

There are no prerequisites

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

  • Shirley, P., Marschner, S.: Fundamentals of Computer Graphics. CRC Press. 2009.
  • Szeliski, R.: Computer Vision: Algorithms and Applications, Springer. 2010.
  • Bradski, G. and Kaehler, A.: Learning OpenCV: Computer Vision with the OpenCV Library, O'Reilly. 2008.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Výuka není kontrolována.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

    Syllabus of lectures:
    1. introduction to CP, light and color
    2. photography, optics, physics, sensors, noise
    3. visual perception, natural image statistics
    4. image blending
    5. color to gray
    6. HDR acquisition and display
    7. HDR tone mapping and inverse tone mapping
    8. image registration for CP
    9. computational illumination, dual photography, relighting
    10. image and video quality assessment
    11. lightfields, synthetic aperture
    12. npr and cae
    13. computational video
    14. image editing software, guests and reserve

Aims

The aim is to introduce computational photography methods (http://cphoto.fit.vutbr.cz/) and to get acquainted with the principles of mathematics and computer science in the field.

Specification of controlled education, way of implementation and compensation for absences

There are no checked study.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MBI , any year of study, summer semester, 5 credits, elective
    branch MPV , any year of study, summer semester, 5 credits, elective
    branch MGM , any year of study, summer semester, 5 credits, elective
    branch MSK , any year of study, summer semester, 5 credits, elective
    branch MIS , any year of study, summer semester, 5 credits, elective
    branch MBS , any year of study, summer semester, 5 credits, elective
    branch MIN , any year of study, summer semester, 5 credits, elective
    branch MMI , any year of study, summer semester, 5 credits, elective
    branch MMM , any year of study, summer semester, 5 credits, elective

eLearning