Scaling law for computational imaging using spherical optics

Oliver S. Cossairt*, Daniel Miau, Shree K. Nayar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

The resolution of a camera system determines the fidelity of visual features in captured images. Higher resolution implies greater fidelity and, thus, greater accuracy when performing automated vision tasks, such as object detection, recognition, and tracking. However, the resolution of any camera is fundamentally limited by geometric aberrations. In the past, it has generally been accepted that the resolution of lenses with geometric aberrations cannot be increased beyond a certain threshold. We derive an analytic scaling law showing that, for lenses with spherical aberrations, resolution can be increased beyond the aberration limit by applying a postcapture deblurring step. We then show that resolution can be further increased when image priors are introduced. Based on our analysis, we advocate for computational camera designs consisting of a spherical lens shared by several small planar sensors. We show example images captured with a proof-of-concept gigapixel camera, demonstrating that high resolution can be achieved with a compact form factor and low complexity. We conclude with an analysis on the trade-off between performance and complexity for computational imaging systems with spherical lenses.

Original languageEnglish (US)
Pages (from-to)2540-2553
Number of pages14
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume28
Issue number12
DOIs
StatePublished - Dec 1 2011

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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