activity
20172021
most citedOnline Convolutional Dictionary Learning for Multimodal Imaging

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Fast and High-Quality Blind Multi-Spectral Image Pansharpening

Lantao Yu, Dehong Liu, Hassan Mansour +1

Blind pansharpening addresses the problem of generating a high spatial-resolution multi-spectral (HRMS) image given a low spatial-resolution multi-spectral (LRMS) image with the gu…

cs.CV2018

Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging

Hassan Mansour, Dehong Liu, Ulugbek S. Kamilov +1

A common problem that arises in radar imaging systems, especially those mounted on mobile platforms, is antenna position ambiguity. Approaches to resolve this ambiguity and correct…

cs.CV2017

Accelerated Image Reconstruction for Nonlinear Diffractive Imaging

Yanting Ma, Hassan Mansour, Dehong Liu +2

The problem of reconstructing an object from the measurements of the light it scatters is common in numerous imaging applications. While the most popular formulations of the proble…

cs.CV20171 cited

Online Convolutional Dictionary Learning for Multimodal Imaging

Kevin Degraux, Ulugbek S. Kamilov, Petros T. Boufounos +1

Computational imaging methods that can exploit multiple modalities have the potential to enhance the capabilities of traditional sensing systems. In this paper, we propose a new me…

cs.CV2017

SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering

Hsiou-Yuan Liu, Dehong Liu, Hassan Mansour +3

Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we des…