NIR spectral imaging data of Norway spruce

This folder includes near-infrared (NIR) spectral imaging data collected on September 30, 2022 at VTT Technical Research Centre of Finland by Mikko Mäkelä (VTT), Patrik Ahvenainen (Aalto University) and Enriqueta Noriega Benitez (Aalto University). The imaged sample is the same as sample "Dry A" in X-ray scattering experiments done at ID02/ESRF on July 1, 2021 (published as a separate record).

The dataset contains hyperspectral image data in raw binary format together with calibration files, metadata, and preview images. Each hyperspectral cube consists of 619 lines, with a spatial resolution of 384 pixels (samples) by 288 spectral bands. The data is provided as .raw files with corresponding .hdr and .log files. The .hdr files include the acquisition parameters, such as sensor type, acquisition date and time, frame rate, binning, instrument temperatures, as well as the wavelength axis  and full width at half maximum (FWHM) of each band. The .log files document the recording status and dropped frame information, this dataset had no frames lost during acquisition.

For each measurement, the data files includes the primary hyperspectral data cube together with the corresponding dark and white reference measurements, all provided as .raw files with their associated .hdr and .log files. In addition, a .png image is provided to show the captured scene. Alongside the capture files, each measurement also includes a calibration file with additional instrument calibration data, and a metadata file with acquisition-related information.

The dataset is organized in two, XRAY_Dry_A and XRAY_FOV, both of which follow the same structure and contain their respective raw data cubes, calibration files, metadata, and preview images.  The XRAY_Dry_A files correspond to the “Dry A” wood sample, imaged as described above, while the FOV files contain a field-of-view reference measurement with the same acquisition setup. A separate .html document is provided that contains the Python code used to preprocess the raw files and to perform PCA and clustering with visualizations of the results.

 For further details on the experimental setup, data processing, and application, please refer to [add reference/publication].