Course detail

Computational Photography

FIT-VYFAcad. year: 2023/2024

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.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Martin Čadík, Ph.D.

Department

Department of Computer Graphics and Multimedia (UPGM)

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

  1. Project proposals
  2. Project assignments
  3. --
  4. --
  5. Consultations after the lecture - literature
  6. --
  7. Consultations after the lecture - implementation
  8. --
  9. Consultations after the lecture - testing
  10. --
  11. WRITTEN EXAM
  12. Finished implementations
  13. Presentations of assignments, final reports

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.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Radke, R.: Computer Vision for Visual Effects. Cambridge university press.  2013.
Szeliski, R.: Computer Vision: Algorithms and Applications, Springer. 2010.
Shirley, P., Marschner, S.: Fundamentals of Computer Graphics. CRC Press. 2009.

Recommended literature

Not applicable.

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBS , 0 year of study, summer semester, elective
    branch MPV , 0 year of study, summer semester, elective
    branch MIS , 0 year of study, summer semester, elective
    branch MIN , 0 year of study, summer semester, elective
    branch MGM , 0 year of study, summer semester, elective
    branch MBI , 0 year of study, summer semester, elective
    branch MSK , 0 year of study, summer semester, elective
    branch MMM , 0 year of study, summer semester, elective

  • Programme MITAI Master's

    specialization NISY , 0 year of study, summer semester, elective
    specialization NSPE , 0 year of study, summer semester, elective
    specialization NBIO , 0 year of study, summer semester, elective
    specialization NSEN , 0 year of study, summer semester, elective
    specialization NVIZ , 0 year of study, summer semester, elective
    specialization NGRI , 0 year of study, summer semester, elective
    specialization NADE , 0 year of study, summer semester, elective
    specialization NISD , 0 year of study, summer semester, elective
    specialization NMAT , 0 year of study, summer semester, elective
    specialization NSEC , 0 year of study, summer semester, elective
    specialization NISY up to 2020/21 , 0 year of study, summer semester, elective
    specialization NCPS , 0 year of study, summer semester, elective
    specialization NHPC , 0 year of study, summer semester, elective
    specialization NNET , 0 year of study, summer semester, elective
    specialization NMAL , 0 year of study, summer semester, elective
    specialization NVER , 0 year of study, summer semester, elective
    specialization NIDE , 0 year of study, summer semester, elective
    specialization NEMB , 0 year of study, summer semester, elective
    specialization NEMB up to 2021/22 , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Martin Čadík, Ph.D.

Syllabus

  1. introduction to CP, light and color (slajdy, projekty)
  2. photography, optics, physics, sensors, noise (slajdy)
  3. visual perception, natural image statistics (slajdy)
  4. image blending (slajdy)
  5. Color, color spaces, color transfer, color-to-grayscale image conversions (slajdy)
  6. High dynamic range (HDR) imaging - acquisition, storage and display (slajdy, HDR skript)
  7. High dynamic range (HDR) imaging - tone mapping, inverse tone mapping (slajdy)
  8. Image registration for computational photography (slajdy)
  9. Computational illumination, dual photography, illumination changes (slajdy)
  10. Image and video quality metrics (slajdy)
  11. Omnidirectional camera, lightfields, synthetic aperture (slajdy)
  12. Non-photorealistic camera, computational aesthetics (slajdy)
  13. Computational video, GraphCuts, editing software, guests

Project

26 hod., compulsory

Teacher / Lecturer

doc. Ing. Martin Čadík, Ph.D.