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arXiv · 1703.09880

Novel Structured Low-rank algorithm to recover spatially smooth exponential image time series

Arvind Balachandrasekaran·Mathews Jacob
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Abstract

We propose a structured low rank matrix completion algorithm to recover a time series of images consisting of linear combination of exponential parameters at every pixel, from under-sampled Fourier measurements. The spatial smoothness of these parameters is exploited along with the exponential structure of the time series at every pixel, to derive an annihilation relation in the $k-t$ domain. This annihilation relation translates into a structured low rank matrix formed from the $k-t$ samples. We demonstrate the algorithm in the parameter mapping setting and show significant improvement over state of the art methods.

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Arvind Balachandrasekaran, Mathews Jacob. 2017-03-29. Novel Structured Low-rank algorithm to recover spatially smooth exponential image time series. https://arxiv.org/abs/1703.09880

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