18 citations · 63 across the 14 of their papers we have counts for
17 papers
Broadband Wide Field of View Imaging with Computational Mirrors
Vishwanath Saragadam, Niki Nezakati, Amit Roy-Chowdhury +1
Traditional glass-based optics are typically optimized for narrow spectral bands, such as the visible (400-700nm) or shortwave infrared (1000-1800nm). While the emergence of VIS-SW…
Provable and Robust Wavefront Sensing via Self-Reference Interferometry
Nebiyou Yismaw, Vishwanath Saragadam, Aswin C. Sankaranarayanan +1
Wavefront sensing involves estimating the phase and intensity of light, enabling a wide range of imaging applications, from adaptive optics and astronomy to biomedical imaging. Sin…
Thermal is Always Wild: Characterizing and Addressing Challenges in Thermal-Only Novel View Synthesis
M. Kerem Aydin, Vishwanath Saragadam, Emma Alexander
Thermal cameras provide reliable visibility in darkness and adverse conditions, but thermal imagery remains significantly harder to use for novel view synthesis (NVS) than visible-…
Thermal Spread Functions (TSF): Physics-guided Material Classification
Aniket Dashpute, Vishwanath Saragadam, Emma Alexander +4
Robust and non-destructive material classification is a challenging but crucial first-step in numerous vision applications. We propose a physics-guided material classification fram…
WIRE: Wavelet Implicit Neural Representations
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan +3
Implicit neural representations (INRs) have recently advanced numerous vision-related areas. INR performance depends strongly on the choice of the nonlinear activation function emp…
Foveated Thermal Computational Imaging in the Wild Using All-Silicon Meta-Optics
Vishwanath Saragadam, Zheyi Han, Vivek Boominathan +7
Foveated imaging provides a better tradeoff between situational awareness (field of view) and resolution and is critical in long-wavelength infrared regimes because of the size, we…
TITAN: Bringing The Deep Image Prior to Implicit Representations
Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi +6
We study the interpolation capabilities of implicit neural representations (INRs) of images. In principle, INRs promise a number of advantages, such as continuous derivatives and a…
PSF: Polarized Spiral Point Spread Function for Single-Shot 3D Sensing
Bhargav Ghanekar, Vishwanath Saragadam, Dushyant Mehra +3
We propose a compact snapshot monocular depth estimation technique that relies on an engineered point spread function (PSF). Traditional approaches used in microscopic super-resolu…
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…
MINER: Multiscale Implicit Neural Representations
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan +2
We introduce a new neural signal model designed for efficient high-resolution representation of large-scale signals. The key innovation in our multiscale implicit neural representa…
Programmable Spectral Filter Arrays using Phase Spatial Light Modulator
Vishwanath Saragadam, Vijay Rengarajan, Ryuichi Tadano +4
Spatially varying spectral modulation can be implemented using a liquid crystal spatial light modulator (SLM) since it provides an array of liquid crystal cells, each of which can…
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…
KRISM --- Krylov Subspace-based Optical Computing of Hyperspectral Images
Vishwanath Saragadam, Aswin C. Sankaranarayanan
We present an adaptive imaging technique that optically computes a low-rank approximation of a scene's hyperspectral image, conceptualized as a matrix. Central to the proposed tech…
Cross-scale predictive dictionaries
Vishwanath Saragadam, Xin Li, Aswin Sankaranarayanan
Sparse representations using data dictionaries provide an efficient model particularly for signals that do not enjoy alternate analytic sparsifying transformations. However, solvin…