Research Papers: Imaging

Comparison of super-resolution algorithms applied to retinal images

[+] Author Affiliations
Damber Thapa

University of Waterloo, School of Optometry and Vision Science, Waterloo, Ontario N2L 3G1, Canada

Kaamran Raahemifar

Ryerson University, Department of Electrical and Computer Engineering, Toronto, Ontario M5B 2K3, Canada

William R. Bobier

University of Waterloo, School of Optometry and Vision Science, Waterloo, Ontario N2L 3G1, Canada

Vasudevan Lakshminarayanan

University of Waterloo, School of Optometry and Vision Science, Waterloo, Ontario N2L 3G1, Canada

University of Waterloo, Departments of Physics and Electrical and Computer Engineering, Waterloo, Ontario N2L 3G1, Canada

University of Michigan, Department of Physics and Department of Electrical Engineering and Computer Science, Ann Arbor, Michigan 48104

J. Biomed. Opt. 19(5), 056002 (May 01, 2014). doi:10.1117/1.JBO.19.5.056002
History: Received August 13, 2013; Revised December 10, 2013; Accepted March 31, 2014
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Abstract.  A critical challenge in biomedical imaging is to optimally balance the trade-off among image resolution, signal-to-noise ratio, and acquisition time. Acquiring a high-resolution image is possible; however, it is either expensive or time consuming or both. Resolution is also limited by the physical properties of the imaging device, such as the nature and size of the input source radiation and the optics of the device. Super-resolution (SR), which is an off-line approach for improving the resolution of an image, is free of these trade-offs. Several methodologies, such as interpolation, frequency domain, regularization, and learning-based approaches, have been developed over the past several years for SR of natural images. We review some of these methods and demonstrate the positive impact expected from SR of retinal images and investigate the performance of various SR techniques. We use a fundus image as an example for simulations.

© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Damber Thapa ; Kaamran Raahemifar ; William R. Bobier and Vasudevan Lakshminarayanan
"Comparison of super-resolution algorithms applied to retinal images", J. Biomed. Opt. 19(5), 056002 (May 01, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.5.056002


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