Computational Photography

Course description:
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. This course covers fundamentals and applications of hardware and software techniques, with an emphasis on software methods. We will study many interesting, recent image based algorithms and implement them to the degree that is possible.

We will cover topics such as

  • Cameras and image formation
  • Image stitching / completion / inpainting
  • Texture synthesis, super-resolution, denoising.
  • Light fields
  • Image based lighting and rendering
  • High dynamic range
  • Intrinsic Images
  • Coded aperture photography
  • Modeling and synthesis using Internet data
  • … more interesting topics.

Tentative Syllabus 2016-2017:

Class DateContentsDetailsLecture notesLab
6 October, ThuIntroductionComputational Photography Overview. Details about the course.Lecture 1Lab0: Get familiar with Photography concepts.
D.P. Applets
13 October, ThuDigital Photography, Image processing pipeline.Digital Camera, Basic Optics, Sensor, Demosaicing, White Balance, Gamma Correction, JPEG compresion.Lecture 2Lab 1
20 October, ThuComputational Imaging IHDR, TMO, Burst Photography. ConfocalLecture 3Lab 2 sec1 sec2 sec3 sec4
3 Novemeber, ThuComputational Imaging IIPanoramas,Homographies, Warping, mosaics.Lecture 4Lab 3
10 Novemeber, ThuComputational Imaging IIIInternet data and Photo-collectionsLecture 5Lab 4
17 November, ThuComputational IlluminationTime of Flight, Light Stage, Photometric Stereo.
Lecture 6Lab 5
24 November, ThuCoded AperturesBlur. Deconvolution. Coded Apertures. Focal Sweep. Lecture 7Lab 6
1 December, ThuCoded ExposuresFlutter Shutter. Parabolic Sweep.Lecture 8No Lab
8 December, ThuLight FieldsDefinition, Capture, and Applications.Lecture 9Lab 7
15 December, ThuCompressive ImagingLight Field extensions. Compressive Sensing. Lecture 10Choose paper for seminar
12 January, ThuComputational DisplaysComputational Displays, Human Vision System.Lecture 11No Lab
19 January, ThuStudent PresentationsList of papers Lab 8
26 January, ThuFemtophotography and Transient RenderingFemtophotography, Transient Rendering.Lecture 12
2 Feburary, ThuLight Transport & Review & ClosureLight Trasport Matrix. Examples of Light Transport Matrices. Operations on Light Transport Matrix. Optical Programming. Recapitulation, Feedback, Closure§Lecture 13Marking Lab 8


Acknowledgements

Some of the materials used in class build on that from other instructors. In particular, we will use some materials from Gordon Wetzstein, Marc Levoy, Fredo Durand, Ramesh Raskar, Shree Nayar, and Alexei A. Efros, who in turn uses materials from Steve Seitz, Rick Szeliski, Paul Debevec, Stephen Palmer, Paul Heckbert, David Forsyth, Steve Marschner and others. Many thanks to them for sharing their work and knowledge.

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