Performance comparison of COTS-based hyperspectral imagers using detailed point spread function measurements

Hyperspectral imaging is a rapidly growing field that utilizes a diverse range of camera designs. It has been demonstrated that hyperspectral cameras can be constructed from commercial off-the-shelf (COTS) components, offering the potential for low-cost and widespread use. However, these COTS-based systems may face performance limitations due to optics not being optimized for hyperspectral purposes. Characterizing and comparing the performance of hyperspectral cameras is complex, a challenge recognized by the ongoing development of the IEEE P4001 standard. Specifically, the spatial coregistration among different spectral bands is crucial for the quality and integrity of the recorded spectra in each pixel. The proper evaluation of coregistration and resolution necessitates the measurement of the point spread function for each band. We use measurements of the full 2D sampling point spread function (SPSF) to compare the performance of two hyperspectral imagers (HSIs) built from COTS components: the engineering model of the hyperspectral camera onboard the Hyperspectral Cubesat for Ocean Observation-1 cubesat and an extremely compact HSI developed for drone flights. In addition, the line spread functions across and along the track, keystone distortion, and coregistration errors are derived from the SPSFs. A simplified measurement scheme is also tried and found to provide fair accuracy for the tested cameras. The results highlight the importance of measuring the spatial SPSF for characterizing and comparing different hyperspectral cameras. Results also show that good spectral integrity can be achieved through spatial binning, which of course requires a tradeoff against spatial resolution. Nonetheless, it is evident that such low-cost systems can offer useful capabilities.

Authors

Institutions

Publication Details

Journal
Journal of Applied Remote Sensing
Published
2024-10-31
DOI
https://doi.org/10.1117/1.jrs.18.047503
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance comparison of COTS-based hyperspectral imagers using detailed point spread function measurements

Marie Bøe Henriksen, T. Skauli, Gard Momrak Selnesaunet
Journal of Applied Remote Sensing
Remote-Sensing Image Classification
article

Performance comparison of COTS-based hyperspectral imagers using detailed point spread function measurements

Marie Bøe Henriksen, T. Skauli, Gard Momrak Selnesaunet
article en

Abstract

Hyperspectral imaging is a rapidly growing field that utilizes a diverse range of camera designs. It has been demonstrated that hyperspectral cameras can be constructed from commercial off-the-shelf (COTS) components, offering the potential for low-cost and widespread use. However, these COTS-based systems may face performance limitations due to optics not being optimized for hyperspectral purposes. Characterizing and comparing the performance of hyperspectral cameras is complex, a challenge recognized by the ongoing development of the IEEE P4001 standard. Specifically, the spatial coregistration among different spectral bands is crucial for the quality and integrity of the recorded spectra in each pixel. The proper evaluation of coregistration and resolution necessitates the measurement of the point spread function for each band. We use measurements of the full 2D sampling point spread function (SPSF) to compare the performance of two hyperspectral imagers (HSIs) built from COTS components: the engineering model of the hyperspectral camera onboard the Hyperspectral Cubesat for Ocean Observation-1 cubesat and an extremely compact HSI developed for drone flights. In addition, the line spread functions across and along the track, keystone distortion, and coregistration errors are derived from the SPSFs. A simplified measurement scheme is also tried and found to provide fair accuracy for the tested cameras. The results highlight the importance of measuring the spatial SPSF for characterizing and comparing different hyperspectral cameras. Results also show that good spectral integrity can be achieved through spatial binning, which of course requires a tradeoff against spatial resolution. Nonetheless, it is evident that such low-cost systems can offer useful capabilities.

Journal of Applied Remote SensingVol. 18(04)
University of Oslo (NO), Norwegian University of Science and Technology (NO)
Openalex Percentile: Top 70%
Remote-Sensing Image Classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.