Abstract

Algorithms that use optical system diversity to improve multiplexed image reconstruction from multiple low-resolution images are analyzed and demonstrated. Compared with systems using identical imagers, systems using additional lower-resolution imagers can have improved accuracy and computation. The diverse system is not sensitive to boundary conditions and can take full advantage of improvements that decrease noise and allow an increased number of bits per pixel to represent spatial information in a scene.

© 2006 Optical Society of America

Multiaperture imaging

Premchandra M. Shankar, William C. Hasenplaugh, Rick L. Morrison, Ronald A. Stack, and Mark A. Neifeld
Appl. Opt. 45(13) 2871-2883 (2006)

Adaptive flat multiresolution multiplexed computational imaging architecture utilizing micromirror arrays to steer subimager fields of view

Marc P. Christensen, Vikrant Bhakta, Dinesh Rajan, Tejaswini Mirani, Scott C. Douglas, Sally L. Wood, and Michael W. Haney
Appl. Opt. 45(13) 2884-2892 (2006)

Adaptive framework for robust high-resolution image reconstruction in multiplexed computational imaging architectures

Noha A. El-Yamany, Panos E. Papamichalis, and Marc P. Christensen
Appl. Opt. 47(10) B117-B127 (2008)

Impact of measurement precision and noise on superresolution image reconstruction

Sally L. Wood, Shu-Ting Lee, Gao Yang, Marc P. Christensen, and Dinesh Rajan
Appl. Opt. 47(10) B128-B138 (2008)

Characteristics of infrared imaging systems that benefit from superresolution reconstruction

Keith Krapels, Ronald G. Driggers, Eddie Jacobs, Stephen Burks, and Susan Young
Appl. Opt. 46(21) 4594-4603 (2007)