26 citations · 45 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
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…
Feature Fusion via Dual-resolution Compressive Measurement Matrix Analysis For Spectral Image Classification
Juan Marcos Ramirez, Jose Ignacio Martinez-Torre, Henry Arguello
In the compressive spectral imaging (CSI) framework, different architectures have been proposed to recover high-resolution spectral images from compressive measurements. Since CSI…