Code and data for: Interpolant-based demosaicing routines for dual-mode visible/near-infrared imaging systems
Cite this dataset
Blair, Steven; Gruev, Viktor (2022). Code and data for: Interpolant-based demosaicing routines for dual-mode visible/near-infrared imaging systems [Dataset]. Dryad. https://doi.org/10.5061/dryad.fj6q573xj
Abstract
Dual-mode visible/near-infrared imaging systems, including a bioinspired six-channel design and more conventional four-channel implementations, have transitioned from a niche in surveillance to general use in machine vision. However, the demosaicing routines that transform the raw images from these sensors into processed images that can be consumed by humans or computers rely on assumptions that may not be appropriate when the two portions of the spectrum contribute different information about a scene. A solution can be found in a family of demosaicing routines that utilize interpolating polynomials and splines of different dimensionalities and orders to process images with minimal assumptions.
Methods
The steps used to collect and process the data in this dataset have been documented in the associated manuscript.
Usage notes
The information needed to use the data in this dataset has been provided in the associated README files.
Funding
United States Air Force, Award: FA9550-18-1-0278
Congressionally Directed Medical Research Programs, Award: W81XWH-19-1-0299
National Science Foundation, Award: 2030421
Office of Naval Research, Award: N00014-19-1-2400
Office of Naval Research, Award: N00014-21-1-2177