Multiaperture imaging
Applied Optics, Vol. 45, Issue 13, pp. 2871-2883 (2006)
http://dx.doi.org/10.1364/AO.45.002871
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Abstract
We study the reconstruction of a high-resolution image from multiple low-resolution images by using a nonlinear iterative backprojection algorithm. We exploit diversities in the imaging channels, namely, the number of imagers, magnification, position, rotation, and fill factor, to undo the degradation caused by the optical blur, pixel blur, and additive noise. We quantify the improvements gained by these diversities in the reconstruction process and discuss the trade-off among system parameters. As an example, for a system in which the pixel size is matched to the diffraction-limited optical blur size at a moderate detector noise level, we can reduce the reconstruction root-mean-square error by
© 2006 Optical Society of America
OCIS Codes
(100.0100) Image processing : Image processing
(100.3020) Image processing : Image reconstruction-restoration
(100.6640) Image processing : Superresolution
(110.0110) Imaging systems : Imaging systems
(110.1220) Imaging systems : Apertures
ToC Category:
Image Reconstruction
History
Original Manuscript: August 10, 2005
Revised Manuscript: October 27, 2005
Manuscript Accepted: October 23, 2005
Citation
Premchandra M. Shankar, William C. Hasenplaugh, Rick L. Morrison, Ronald A. Stack, and Mark A. Neifeld, "Multiaperture imaging," Appl. Opt. 45, 2871-2883 (2006)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-45-13-2871
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