65 citations · 269 across the 30 of their papers we have counts for
8 papers · 1 filter
Joint Radar-Communications Processing from a Dual-Blind Deconvolution Perspective
Edwin Vargas, Kumar Vijay Mishra, Roman Jacome +2
We consider a general spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown at the receiver. In this \textit…
A fast and Accurate Similarity-constrained Subspace Clustering Framework for Unsupervised Hyperspectral Image Classification
Carlos Hinojosa, Esteban Vera, Henry Arguello
Accurate land cover segmentation of spectral images is challenging and has drawn widespread attention in remote sensing due to its inherent complexity. Although significant efforts…
Deep Coded Aperture Design: An End-to-End Approach for Computational Imaging Tasks
Jorge Bacca, Tatiana Gelvez, Henry Arguello
Covering from photography to depth and spectral estimation, diverse computational imaging (CI) applications benefit from the versatile modulation of coded apertures (CAs). The ligh…
Time-Multiplexed Coded Aperture Imaging: Learned Coded Aperture and Pixel Exposures for Compressive Imaging Systems
Edwin Vargas, Julien N. P. Martel, Gordon Wetzstein +1
Compressive imaging using coded apertures (CA) is a powerful technique that can be used to recover depth, light fields, hyperspectral images and other quantities from a single snap…
LADMM-Net: An Unrolled Deep Network For Spectral Image Fusion From Compressive Data
Juan Marcos Ramírez, José Ignacio Martínez Torre, Henry Arguello Fuentes
Image fusion aims at estimating a high-resolution spectral image from a low-spatial-resolution hyperspectral image and a low-spectral-resolution multispectral image. In this regard…
Subspace-Based Feature Fusion From Hyperspectral And Multispectral Image For Land Cover Classification
Juan Ramírez, Héctor Vargas, José Ignacio Martínez +1
In remote sensing, hyperspectral (HS) and multispectral (MS) image fusion have emerged as a synthesis tool to improve the data set resolution. However, conventional image fusion me…
Compressive Spectral Image Reconstruction using Deep Prior and Low-Rank Tensor Representation
Jorge Bacca, Yesid Fonseca, Henry Arguello
Compressive spectral imaging (CSI) has emerged as an alternative spectral image acquisition technology, which reduces the number of measurements at the cost of requiring a recovery…
Covariance Estimation from Compressive Data Partitions using a Projected Gradient-based Algorithm
Jonathan Monsalve, Juan Ramirez, Iñaki Esnaola +1
Compressive covariance estimation has arisen as a class of techniques whose aim is to obtain second-order statistics of stochastic processes from compressive measurements. Recently…