65 citations · 88 across the 11 of their papers we have counts for
5 papers · 1 filter
Mixture-Net: Low-Rank Deep Image Prior Inspired by Mixture Models for Spectral Image Recovery
Tatiana Gelvez-Barrera, Jorge Bacca, Henry Arguello
This paper proposes a non-data-driven deep neural network for spectral image recovery problems such as denoising, single hyperspectral image super-resolution, and compressive spect…
Deep Optical Coding Design in Computational Imaging
Henry Arguello, Jorge Bacca, Hasindu Kariyawasam +10
Computational optical imaging (COI) systems leverage optical coding elements (CE) in their setups to encode a high-dimensional scene in a single or multiple snapshots and decode it…
Deep Coding Patterns Design for Compressive Near-Infrared Spectral Classification
Jorge Bacca, Alejandra Hernandez-Rojas, Henry Arguello
Compressive spectral imaging (CSI) has emerged as an attractive compression and sensing technique, primarily to sense spectral regions where traditional systems result in highly co…
DUF: Deep Coded Aperture Design and Unrolling Algorithm for Compressive Spectral Image Fusion
Roman Jacome, Jorge Bacca, Henry Arguello
Compressive spectral imaging (CSI) has attracted significant attention since it employs synthetic apertures to codify spatial and spectral information, sensing only 2D projections…
JR2net: A Joint Non-Linear Representation and Recovery Network for Compressive Spectral Imaging
Brayan Monroy, Jorge Bacca, Henry Arguello
Deep learning models are state-of-the-art in compressive spectral imaging (CSI) recovery. These methods use a deep neural network (DNN) as an image generator to learn non-linear ma…