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Published on: August 16, 2012
Computational cameras: convergence of optics and processing
1Department of Computer Science, Columbia University, New York, NY 10027, USA. changyin@cs.columbia.edu
Summary
Computational cameras use optics and processing to capture images beyond traditional limits. This survey categorizes designs by coding methods and light field representation for enhanced visual information capture.
Area of Science:
- Computer Vision
- Optical Engineering
- Image Processing
Background:
- Computational imaging has rapidly advanced, offering capabilities beyond conventional cameras.
- Computational cameras integrate optics and processing to capture richer visual information.
Purpose of the Study:
- To provide a comprehensive survey of computational camera designs.
- To categorize computational cameras based on their information encoding strategies.
- To frame computational cameras as light field projections.
Main Methods:
- Taxonomic classification of computational camera designs by coding approaches (object side, pupil plane, sensor side, illumination, arrays, unconventional systems).
- Utilizing light field representation as a unifying framework to describe camera designs.
- Analyzing optical device transformations of light fields.
Main Results:
- A taxonomy categorizing computational cameras based on coding strategies.
- Demonstration of light field representation as a tool to understand camera designs.
- Illustration of how optical elements encode visual information.
Conclusions:
- Computational cameras offer advanced capabilities by encoding more visual information.
- Light field representation provides a generalized perspective on computational camera design.
- Understanding optical transforms is key to designing effective computational cameras.
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