Deep coded aperture design: An end-to-end approach for computational imaging tasks

J Bacca, T Gelvez-Barrera… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Covering from photography to depth and spectral estimation, diverse computational imaging
(CI) applications benefit from the versatile modulation of coded apertures (CAs). The …

DUF: Deep Coded Aperture Design and Unrolling Algorithm for Compressive Spectral Image Fusion

R Jacome, J Bacca, H Arguello - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Compressive spectral imaging (CSI) has attracted significant attention since it employs
synthetic apertures to codify spatial and spectral information, sensing only 2D projections of …

Joint nonlocal, spectral, and similarity low-rank priors for hyperspectral–multispectral image fusion

T Gelvez-Barrera, H Arguello… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The fusion of a low-spatial-and-high-spectral resolution hyperspectral image (HSI) with a
high-spatial-and-low-spectral resolution multispectral image (MSI) allows synthesizing a …

[HTML][HTML] LADMM-Net: An unrolled deep network for spectral image fusion from compressive data

JM Ramirez, JI Martínez-Torre, H Arguello - Signal Processing, 2021 - Elsevier
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 …

Hyperspectral and multispectral image fusion addressing spectral variability by an augmented linear mixing model

A Camacho, E Vargas, H Arguello - International Journal of …, 2022 - Taylor & Francis
The fusion of hyperspectral (HS) and multispectral (MS) images with complementary high
spectral and high spatial resolution information has been successfully applied to improve …

Nonlocal low-rank plus deep denoising prior for robust image compressed sensing reconstruction

Y Li, L Gao, S Hu, G Gui, CY Chen - Expert Systems with Applications, 2023 - Elsevier
It is challenging for current compressive sensing (CS) approaches to reconstruct image from
compressed observations with impulsive noise and outliers, termed robust image CS …

Multiply complementary priors for image compressive sensing reconstruction in impulsive noise

Y Li, F Xiao, W Liang, L Gui - ACM Transactions on Multimedia …, 2024 - dl.acm.org
Impulsive noise is always present in real-world image Compressive Sensing (CS)
acquisition systems, where existing CS reconstruction performance may seriously …

Multi-Sensor Image Feature Fusion via Subspace-Based Approach Using -Gradient Regularization

H Vargas, J Ramírez, S Pinilla… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Image fusion is a technique of combining two or more images into a single image which is
more informative from an interpretation point of view. With the rapid development of different …

Compressive spectral image fusion via a single aperture high throughput imaging system

H Rueda-Chacon, F Rojas, H Arguello - Scientific Reports, 2021 - nature.com
Spectral image fusion techniques combine the detailed spatial information of a multispectral
(MS) image and the rich spectral information of a hyperspectral (HS) image into a high …

Mixture-net: Low-rank deep image prior inspired by mixture models for spectral image recovery

T Gelvez-Barrera, J Bacca, H Arguello - Signal Processing, 2024 - Elsevier
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 …