7 citations · 7 across the 1 of their papers we have counts for
5 papers
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors
Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan +1
DeepTensor is a computationally efficient framework for low-rank decomposition of matrices and tensors using deep generative networks. We decompose a tensor as the product of low-r…
Thermal Image Processing via Physics-Inspired Deep Networks
Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan +1
We introduce DeepIR, a new thermal image processing framework that combines physically accurate sensor modeling with deep network-based image representation. Our key enabling obser…
SASSI -- Super-Pixelated Adaptive Spatio-Spectral Imaging
Vishwanath Saragadam, Michael DeZeeuw, Richard Baraniuk +2
We introduce a novel video-rate hyperspectral imager with high spatial, and temporal resolutions. Our key hypothesis is that spectral profiles of pixels in a super-pixel of an over…
On Space-spectrum Uncertainty Analysis for Coded Aperture Systems
Vishwanath Saragadam, Aswin Sankaranarayanan
We introduce and analyze the concept of space-spectrum uncertainty for certain commonly-used designs for spectrally programmable cameras. Our key finding states that, it is impossi…
Programmable Spectrometry -- Per-pixel Classification of Materials using Learned Spectral Filters
Vishwanath Saragadam, Aswin C. Sankaranarayanan
Many materials have distinct spectral profiles. This facilitates estimation of the material composition of a scene at each pixel by first acquiring its hyperspectral image, and sub…