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

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