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4D Frequency Analysis of Computational Cameras for Depth of Field Extension

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dc.contributor.advisor William Freeman Levin, Anat en_US Hasinoff, Samuel W. en_US Freeman, William T. en_US Green, Paul en_US Durand, Fredo en_US
dc.contributor.other Vision 2009-05-08T15:45:09Z 2009-05-08T15:45:09Z 2009-05-08
dc.description.abstract Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundamental tradeoff in photography---wide apertures are important to reduce imaging noise, but they also increase defocus blur. Recent advances in computational imaging modify the acquisition process to extend the DOF through deconvolution. Because deconvolution quality is a tight function of the frequency power spectrum of the defocus kernel, designs with high spectra are desirable. In this paper we study how to design effective extended-DOF systems, and show an upper bound on the maximal power spectrum that can be achieved. We analyze defocus kernels in the 4D light field space and show that in the frequency domain, only a low-dimensional 3D manifold contributes to focus. Thus, to maximize the defocus spectrum, imaging systems should concentrate their limited energy on this manifold. We review several computational imaging systems and show either that they spend energy outside the focal manifold or do not achieve a high spectrum over the DOF. Guided by this analysis we introduce the lattice-focal lens, which concentrates energy at the low-dimensional focal manifold and achieves a higher power spectrum than previous designs. We have built a prototype lattice-focal lens and present extended depth of field results. en_US
dc.format.extent 18 p. en_US
dc.relation.ispartofseries MIT-CSAIL-TR-2009-019 en_US
dc.subject light fields en_US
dc.subject Fourier analysis en_US
dc.subject Computational cameras en_US
dc.subject depth of field en_US
dc.title 4D Frequency Analysis of Computational Cameras for Depth of Field Extension en_US

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