65 citations · 269 across the 30 of their papers we have counts for
12 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…
Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach
Paul Goyes, Edwin Vargas, Claudia Correa +4
Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging. Pre-processing approaches, such as missing trace or shot interpol…
Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications
Jonathan Monsalve, Edwin Vargas, Kumar Vijay Mishra +2
Recent interest in integrated sensing and communications has led to the design of novel signal processing techniques to recover information from an overlaid radar-communications si…
Fast Disparity Estimation from a Single Compressed Light Field Measurement
Emmanuel Martinez, Edwin Vargas, Henry Arguello
The abundant spatial and angular information from light fields has allowed the development of multiple disparity estimation approaches. However, the acquisition of light fields req…
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…
Dual-Blind Deconvolution for Overlaid Radar-Communications Systems
Edwin Vargas, Kumar Vijay Mishra, Roman Jacome +2
The increasingly crowded spectrum has spurred the design of joint radar-communications systems that share hardware resources and efficiently use the radio frequency spectrum. We st…
Multi-dimensional dual-blind deconvolution approach toward joint radar-communications
Roman Jacome, Kumar Vijay Mishra, Edwin Vargas +2
We consider a joint multiple-antenna radar-communications system in a co-existence scenario. Contrary to conventional applications, wherein at least the radar waveform and communic…
PrivHAR: Recognizing Human Actions From Privacy-preserving Lens
Carlos Hinojosa, Miguel Marquez, Henry Arguello +3
The accelerated use of digital cameras prompts an increasing concern about privacy and security, particularly in applications such as action recognition. In this paper, we propose…
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…
Phase Retrieval for Radar Waveform Design
Samuel Pinilla, Kumar Vijay Mishra, Brian M. Sadler +1
The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is…