Mathematics to the Rescue: Addressing Deficiencies in Overhead Imagery Products
A Workshop at the Joint Math Meetings (JMM 2021), Virtual, January 6, 2021
A Workshop at the Joint Math Meetings (JMM 2021), Virtual, January 6, 2021
Overhead imaging or remote sensing is a wide ranging field which uses imagery products acquired by distant sensors to ascertain information of an area or target of interest. Due to low spatial resolution, atmospheric effects, wide ranging collection geometries, and limited labeled data developing generalizable algorithms is difficult. A recent trend has been to move away from traditional statistical and black box deep learning models to techniques which are inspired and informed by rigorous mathematical analysis. These mathematical techniques borrow from theoretical results in geometry, topology, harmonic analysis, and algebra to better capture the intricacies of difficult sensing problems and leverage the limited labeled samples. We will consider a wide problem domain including target and anomaly detection, atmospheric characterization, land cover analysis, and change detection but ask speakers to apply their techniques to well characterized data.
Organizers:
Tim Doster, Pacific Northwest National Laboratory
Adam Attarian, Pacific Northwest National Laboratory
Tegan Emerson, Pacific Northwest National Laboratory
Henry Kvinge, Pacific Northwest National Laboratory
10:00 a.m.
Radiometrically Accurate Spatial Resolution Enhancement of Spectral Imagery for Improved Exploitation.
David Messinger*, Center for Imaging Science, Rochester Institute of Technology
S. Huang, Center for Imaging Science, Rochester Institute of Technology
(1163-78-1304)
11:00 a.m.
Fourier Scattering Transforms as Efficient Feature Extractors.
Wojciech Czaja*, University of Maryland
(1163-42-1554)
1:00 p.m.
Data-Dependent Distances for Hyperspectral Images.
James M Murphy*, Tufts Universiity
(1163-68-261)
1:30 p.m.
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization.
Yifei Lou*, The University of Texas at Dallas
(1163-65-1433)
2:00 p.m.
Modeling Patterns of Life Using Count Time Series Models.
Eric Truslow*, MIT-Lincoln Laboratory
Dimitris Manolakis, MIT-Lincoln Laboratory
(1163-60-1393)
2:30 p.m.
Seismic resonances in dynamic snow environments: modeling climate forcing through singing ice.
Julien Chaput*, University of Texas at El Paso / Pacific Northwest national Laboratory
Richard Aster, Colorado State University
(1163-86-1172)
3:00 p.m.
Spatial-Spectral Data and Unsupervised Autoencoder Training for Hyperspectral Anomaly Detection.
Colin C. Olson*, U.S. Naval Research Laboratory
(1163-57-1071)
3:30 p.m.
Detecting anomalous changes across remote sensing images from different satellites.
Amanda Ziemann*, Los Alamos National Laboratory
Christopher Ren, Los Alamos National Laboratory
James Theiler, Los Alamos National Laboratory
(1163-86-367)
4:00 p.m.
Synthetic Aperture Radar Imaging through a Turbulent Ionosphere.
Mikhail Gilman, North Carolina State University
Semyon Tsynkov*, North Carolina State University
(1163-86-493)