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Proceedings Paper

Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter
Author(s): Donald G. Dansereau; Daniel L. Bongiorno; Oscar Pizarro; Stefan B. Williams
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Paper Abstract

Imaging in low light is problematic as sensor noise can dominate imagery, and increasing illumination or aperture size is not always effective or practical. Computational photography offers a promising solution in the form of the light field camera, which by capturing redundant information offers an opportunity for elegant noise rejection. We show that the light field of a Lambertian scene has a 4D hyperfan-shaped frequency-domain region of support at the intersection of a dual-fan and a hypercone. By designing and implementing a filter with appropriately shaped passband we accomplish denoising with a single all-in-focus linear filter. Drawing examples from the Stanford Light Field Archive and images captured using a commercially available lenselet- based plenoptic camera, we demonstrate that the hyperfan outperforms competing methods including synthetic focus, fan-shaped antialiasing filters, and a range of modern nonlinear image and video denoising techniques. We show the hyperfan preserves depth of field, making it a single-step all-in-focus denoising filter suitable for general-purpose light field rendering. We include results for different noise types and levels, over a variety of metrics, and in real-world scenarios. Finally, we show that the hyperfan’s performance scales with aperture count.

Paper Details

Date Published: 14 February 2013
PDF: 14 pages
Proc. SPIE 8657, Computational Imaging XI, 86570P (14 February 2013); doi: 10.1117/12.2002239
Show Author Affiliations
Donald G. Dansereau, The Univ. of Sydney (Australia)
Daniel L. Bongiorno, The Univ. of Sydney (Australia)
Oscar Pizarro, The Univ. of Sydney (Australia)
Stefan B. Williams, The Univ. of Sydney (Australia)

Published in SPIE Proceedings Vol. 8657:
Computational Imaging XI
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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