4 citations · 4 across the 3 of their papers we have counts for
6 papers
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 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…
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…
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…
Exact Crystalline Structure Recovery in X-ray Crystallography from Coded Diffraction Patterns
Samuel Pinilla, Jorge Bacca, Cesar Vargas +2
X-ray crystallography (XC) is an experimental technique used to determine three-dimensional crystalline structures. The acquired data in XC, called diffraction patterns, is the Fou…
SPRSF: Sparse Phase Retrieval via Smoothing Function
Samuel Pinilla, Jorge Bacca, Henry Arguello
Phase retrieval (PR) is an ill-conditioned inverse problem which can be found in various science and engineering applications. Assuming sparse priority over the signal of interest,…