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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