Title: Novel Structured Low-rank algorithm to recover spatially smooth exponential image time series,
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.