69 citations · 105 across the 23 of their papers we have counts for
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Tomographic Reconstruction using Global Statistical Prior
Preeti Gopal, Ritwick Chaudhry, Sharat Chandran +2
Recent research in tomographic reconstruction is motivated by the need to efficiently recover detailed anatomy from limited measurements. One of the ways to compensate for the incr…
Signal Recovery in Perturbed Fourier Compressed Sensing
Eeshan Malhotra, Himanshu Pandotra, Ajit Rajwade +1
In many applications in compressed sensing, the measurement matrix is a Fourier matrix, i.e., it measures the Fourier transform of the underlying signal at some specified `base' fr…
Optimizing Matrices For Compressed Sensing Using Existing Goodness Measures: Negative Results, And An Alternative
Alankar Kotwal, Ajit Rajwade
The bound that arises out of sparse recovery analysis in compressed sensing involves input signal sparsity and some property of the sensing matrix. An effort has therefore been mad…
Reconstruction Error Bounds for Compressed Sensing under Poisson or Poisson-Gaussian Noise Using Variance Stabilization Transforms
Deepak Garg, Pakshal Bohra, Karthik S. Gurumoorthy +1
Most existing bounds for signal reconstruction from compressive measurements make the assumption of additive signal-independent noise. However in many compressive imaging systems,…