DocumentCode :
2987921
Title :
Gigapixel Computational Imaging
Author :
Cossairt, Oliver S. ; Miau, Daniel ; Nayar, Shree K.
Author_Institution :
Columbia Univ., New York, NY, USA
fYear :
2011
fDate :
8-10 April 2011
Firstpage :
1
Lastpage :
8
Abstract :
Today, consumer cameras produce photographs with tens of millions of pixels. The recent trend in image sensor resolution seems to suggest that we will soon have cameras with billions of pixels. However, the resolution of any camera is fundamentally limited by geometric aberrations. We derive a scaling law that shows that, by using computations to correct for aberrations, we can create cameras with unprecedented resolution that have low lens complexity and compact form factor. In this paper, we present an architecture for gigapixel imaging that is compact and utilizes a simple optical design. The architecture consists of a ball lens shared by several small planar sensors, and a post-capture image processing stage. Several variants of this architecture are shown for capturing a contiguous hemispherical field of view as well as a complete spherical field of view. We demonstrate the effectiveness of our architecture by showing example images captured with two proof-of-concept gigapixel cameras.
Keywords :
computational complexity; computational geometry; image processing; image sensors; ball lens; compact form factor; consumer cameras; geometric aberrations; gigapixel computational imaging; image sensor resolution; lens complexity; planar sensors; post capture image processing stage; Cameras; Image resolution; Lenses; Pixel; Sensor arrays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Photography (ICCP), 2011 IEEE International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-61284-707-8
Type :
conf
DOI :
10.1109/ICCPHOT.2011.5753115
Filename :
5753115
Link To Document :
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