Abstract

In the field of spectroscopy, a splicing correction is a process by which two spectra captured with different sensors in adjacent or overlapping electromagnetic spectrum ranges are smoothly connected. In our study, we extend this concept to the case of reflectance imaging spectroscopy in the visible–near-infrared (VNIR) and short-wave infrared (SWIR), accounting for additional sources of noise that arise at the pixel level. The proposed approach exploits the adaptive fitting of a logistic function to compute correcting coefficients that harmonize the two spectral sets. This short Letter addresses usage conditions and compares results against the existing state of the art.

© 2023 Optica Publishing Group

Scanning-based compressive hyperspectral imaging via spectral-coded illumination

Rui Liu, Ying Xiao, Zhongyuan Wang, Jiayi Ma, and Xin Tian
Opt. Lett. 48(13) 3387-3390 (2023)

Model-based large-dynamic iterative piston correction using extended objects

Zexia Zhang and Bing Dong
Opt. Lett. 48(14) 3681-3684 (2023)

Learning-based correction with Gaussian constraints for ghost imaging through dynamic scattering media

Yang Peng and Wen Chen
Opt. Lett. 48(17) 4480-4483 (2023)

Copper concentrate dual-band joint classification using reflectance hyperspectral images in the VIS-NIR and SWIR bands

Franco Rivas, Francisco Pérez, Claudio Sandoval, Ignacio Sanhueza, Benjamín Sepúlveda, Jorge Yañez, and Sergio Torres
Appl. Opt. 62(12) 2970-2977 (2023)

DiffuserSpec: spectroscopy with Scotch tape

Joseph D. Malone, Neerja Aggarwal, Laura Waller, and Audrey K. Bowden
Opt. Lett. 48(2) 323-326 (2023)