Computational Photography


by dr. Francho Melendez



  • Definitions
  • Content overview and examples
  • Course organization
  • Mild homework for next week

what's computational photography

Computational photography is a relatively new field at the convergence of photography, computer vision, image processing, and computer graphics. Its goal is to overcome the limitations of traditional photography using computational techniques to enhance the way we capture, manipulate, and interact with visual media.

Create photo that could not have been taken by a traditional Camera (?)

Goal: Record a richer, multi-layered visual experience

  • Overcome limitations of today’s cameras

  • Support better post-capture processing

  • Enables new classes of recording the visual signal

  • Synthesize “impossible” photos

Mantis Shrimp possesses the most sophisticated visual system known in Earth

True facts about the mantis shrimp

plenoptic function

  • $L = L(x,y,z, \theta, \phi, \lambda, t)$
  • plenoptic imaging

  • coded photography

  • computational displays

  • capturing light transport

plenoptic imaging (epsilon photography)

coded photography

computational displays

  • 3D Displays
  • Light Field Displays
  • HDR Displays
  • Volumetric Displays

capturing light transport

  • Image Relighting
  • Separate direct from indirect illumination
  • Separate relflectance components
  • Femtophotography

Tentative Syllabus

Some Gurus


this course



  • Get an overview of the field
  • Learn concepts of Digital Photography
  • Understand how different C.P. techniques work at high-level
  • Understand the fundamentals of this techniques


  • Experience with implementing image processing algorithms
  • Experience with the practicalities of Digital Photography
  • Review a technical paper
  • and present it


  • Reflect about the future of Photography
  • Reflect about future applications of Photography
  • Reflect about the importance of cameras at present and future
  • Look at photography with a different mindset

course structure

  • Lectures are compulsory
  • Lecture: Thursday 10:15 - 11:45
  • Lab: Thursday 12:00 - 14:00
  • 15 Lectures
  • 2 NOV Holiday

classes structure

  • First 45 minutes: Overview of the topic, techniques, applications, etc (high level)
  • 3-4 SIGGRAPH Papers
  • Rest: Fundamentals, details, implementation, lab oriented (low level)
  • some time focus on 1 particular paper
  • Introduction to the day's lab.


  • Lab time mostly for marking
  • implementation of some fundamental ideas
  • play with some special type of data

evaluation (tentative)

  • Labs - 85%
    • 1 or 2 weeks labs
    • minus 10% per week for late submission (up to 30%)
    • minimum 50%
  • Paper review - 15%
    • 10 Minutes Presentation

about you

  • Experience with Photography?
  • Python? C++?
  • image processing, CG?
  • feedback, ideas, discussion. Welcome.
  • topics you are interested in?


thursday 16:00 - 18:00

but I should be around 338

credits and references and aditional readings

These slides have been prepared with materials, slides, and discussions from the following.

today's lab

Fundamentals of Digital Photography Applets.
  • Read the descriptions
  • Play around with applets
  • Get an understanding of
    • relationship between aperture and exposure
    • Gamma correction
    • Depht of field
    • Spatial Convolution
    • Color Theory