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@article{Shi2014LightFR, title={Light Field Reconstruction Using Sparsity in the Continuous Fourier Domain}, author={Lixin Shi and Haitham Hassanieh and Abe Davis and Dina Katabi and Fr{\'e}do Durand}, journal={ACM Trans. Graph.}, year={2014}, volume={34}, pages={12:1-12:13} }

- Published 2014 in ACM Trans. Graph.
DOI:10.1145/2682631

Sparsity in the Fourier domain is an important property that enables the dense reconstruction of signals, such as 4D light fields, from a small set of samples. The sparsity of natural spectra is often derived from continuous arguments, but reconstruction algorithms typically work in the discrete Fourier domain. These algorithms usually assume that sparsity derived from continuous principles will hold under discrete sampling. This article makes the critical observation that sparsity is much… CONTINUE READING

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