Logistic splicing correction for VNIR–SWIR reflectance imaging spectroscopy

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.

Relationship between reflectance and degree of polarization in the VNIR-SWIR: A case study on art paintings with polarimetric reflectance imaging spectroscopy

“…This is usually due to a series of factors that include different spectral bandwidths, low signal-to-noise ratio, and misalignments in the imaging setup that cause the BRDF to slightly vary. Spectral splicing is a correction that smoothly connects two spectra affected by spectral jumps [ 45 ], and can be extended to connect VNIR and SWIR hyperspectral images [ 46 ], like in our instance.…”

Full VNIR-SWIR Hyperspectral Imaging Workflow for the Monitoring of Archaeological Textiles

“…Splicing [14] is a spectral correction that is applied whenever two sensors capture information in adjacent or overlapping spectral ranges. What is normally observed at these particular wavelengths is a mismatch in values of the order of 1 − 5%.…”