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Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier Samples
Journal article   Peer reviewed

Off-the-Grid Recovery of Piecewise Constant Images from Few Fourier Samples

Greg Ongie and Mathews Jacob
SIAM journal on imaging sciences, Vol.9(3), pp.1004-1041
2016
DOI: 10.1137/15M1042280
PMCID: PMC6028195
PMID: 29973971
url
https://www.ncbi.nlm.nih.gov/pmc/articles/6028195View
Open Access

Abstract

We introduce a method to recover a continuous domain representation of a piecewise constant two-dimensional image from few low-pass Fourier samples. Assuming the edge set of the image is localized to the zero set of a trigonometric polynomial, we show the Fourier coefficients of the partial derivatives of the image satisfy a linear annihilation relation. We present necessary and sufficient conditions for unique recovery of the image from finite low-pass Fourier samples using the annihilation relation. We also propose a practical two-stage recovery algorithm which is robust to model-mismatch and noise. In the first stage we estimate a continuous domain representation of the edge set of the image. In the second stage we perform an extrapolation in Fourier domain by a least squares two-dimensional linear prediction, which recovers the exact Fourier coefficients of the underlying image. We demonstrate our algorithm on the super-resolution recovery of MRI phantoms and real MRI data from low-pass Fourier samples, which shows benefits over standard approaches for single-image super-resolution MRI.

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