DOI: 10.5281/zenodo.10278731
title: On the use of a consumer-grade 360-degree camera as a radiometer for scientific applications: calibration dataset

description: Studying the geometric distribution of the light field in terms of absolute radiometry required expensive and complex instruments. New types of compact 360-degree cameras have recently appeared on the consumer technology market. Some of these allow users to access raw imagery, offering sensor-level data that can be directly exploited for absolute light quantification. This paves the way for easy-to-use, inexpensive and accessible radiance cameras that can be operated in a wide range of natural environments. 

This dataset presents raw format images captured with the camera Insta360 ONE for its calibration and characterization. These experiments include geometric calibration, relative illumination evaluation, spectral response determination, absolute spectral radiance calibration, as well as linearity and dark frame analysis. In addition, we are providing data from a calibration validation experiment based on co-located measurements of the sky's downward radiance using a 360-degree calibrated camera and a scientific radiometer: the Compact Optical Profiling System (C-OPS, Biospherical Instruments Inc.).

This repository contains raw files as taken by the camera's imaging sensor. In most cases, no data processing has been carried out. The entire data set is contained in a .zip file which includes the following sub-folders (in alphabetical order):



absolute-radiance: data (.dng, .tsv , .hdf5) acquired for absolute spectral radiance calibration

darkframe: DNG raw images taken for dark frame analysis

geometric: DNG images used for the geometric calibration

immersion-factor: DNG images for the calculation of the immersion factor

linearity: DNG images for linearity assessment (gain and exposure time)

relative-illumination: DNG images for roll-off (relative illumination) characterization

relative-spectral-response: data (.asc, .dng) taken for relative spectral response characterization

verification&validation: time series data (.tsv, .dng) of the calibration validation experiment 


Each folder contains a README file explaining the additional subfolders and their files. As you may notice, some of the subfolders are named "lensclose" or "lensfar". They refers to the data acquired with the fish-eye optic assembly that is closer or farther from the top of the 360-degree camera respectively. Some calibrations were performed both in water and in air (geometric calibration, relative-illumination). In that regard, the images were placed in folders refering to "air" and "water". The routines (coded in python) for the data processing can be found in the following Github repository (master_v01) or the Zenodo stored version. The useful scripts are located in the calibration directory, and the README for each folder points to the revelant code for analysis of the files they contain. For additional information, all the methodologies are described in the arXiv preprint. 
description: This research was supported by the SMAART program through the Collaborative Research and Training Experience program (CREATE) of the Natural Sciences and Engineering Council of Canada (NSERC), the Sentinel North program of Université Laval, made possible, in part, thanks to the funding from the Canada First Research Excellence Fund, the Canadian Excellence Research Chair on Remote sensing of Canada's new Arctic frontier, and Marcel Babin Discovery Grant #RGPIN-2020-06384.