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

Tentative Syllabus 2016-2017:

ContentsDetails
IntroductionComputational Photography Overview. Details about the course.
Digital Photography, Image processing pipeline.Digital Camera, Basic Optics, Sensor, Demosaicing, White Balance, Gamma Correction, JPEG compresion.
Computational Imaging IHDR, TMO, Burst Photography. Confocal
Computational Imaging IIPanoramas,Homographies, Warping, mosaics.
Computational Imaging IIIInternet data and Photo-collections
Computational IlluminationTime of Flight, Light Stage, Photometric Stereo.
Coded AperturesBlur. Deconvolution. Coded Apertures. Focal Sweep.
Coded ExposuresFlutter Shutter. Parabolic Sweep.
Light FieldsDefinition, Capture, and Applications.
Compressive ImagingLight Field extensions. Compressive Sensing.
Computational DisplaysComputational Displays, Human Vision System.
Student PresentationsList of papers
Femtophotography and Transient RenderingFemtophotography, Transient Rendering.
Light Transport & Review & ClosureLight Trasport Matrix. Examples of Light Transport Matrices. Operations on Light Transport Matrix. Optical Programming. Recapitulation, Feedback, Closure§


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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