A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes

Abstract

The increased sensitivity of modern hyperspectral line-scanning systems has led to the development of imaging systems that can acquire each line of hyperspectral pixels at very high data rates (in the 200–400 Hz range). These data acquisition rates present an opportunity to acquire full hyperspectral scenes at rapid rates, enabling the use of traditional push-broom imaging systems as low-rate video hyperspectral imaging systems. This paper provides an overview of the design of an integrated system that produces low-rate video hyperspectral image sequences by merging a hyperspectral line scanner, operating in the visible and near infra-red, with a high-speed pan-tilt system and an integrated IMU-GPS that provides system pointing. The integrated unit is operated from atop a telescopic mast, which also allows imaging of the same surface area or objects from multiple view zenith directions, useful for bi-directional reflectance data acquisition and analysis. The telescopic mast platform also enables stereo hyperspectral image acquisition, and therefore, the ability to construct a digital elevation model of the surface. Imaging near the shoreline in a coastal setting, we provide an example of hyperspectral imagery time series acquired during a field experiment in July 2017 with our integrated system, which produced hyperspectral image sequences with 371 spectral bands, spatial dimensions of 1600 × 212, and 16 bits per pixel, every 0.67 s. A second example times series acquired during a rooftop experiment conducted on the Rochester Institute of Technology campus in August 2017 illustrates a second application, moving vehicle imaging, with 371 spectral bands, 16 bit dynamic range, and 1600 × 300 spatial dimensions every second.

Retrieval of Sediment Filling Factor in a Salt Panne from Multi-View Hyperspectral Imagery

“…To collect imagery during the campaign, we used our state-of-the-art hyperspectral imaging system [40]. The hyperspectral imager, a Headwall VNIR Micro-hyperspec High Efficiency E-series [44] (Headwall Photonics, Bolton, MA, USA), is a pushbroom system providing spectral measurements from 400 to 1000 nm with 371 spectral bands and 1600 across-track spatial pixels.…”

“…The imaging system also hosts a Vectornav VN-300 IMU-GPS [46] (VectorNav Technologies, Dallas, TX, USA) to provide pointing information and GPS time-stamps. In the field, the HSI system is placed on top of a BlueSky AL-3 (15 m) telescopic mast [47] (BlueSky Mast, Largo, FL, USA), which can be raised up to 15 m above the ground [40]. The pan-tilt unit integrated into the telescopic mast is capable of imaging a scene from multiple viewing geometries, which allows us to perform HCRF measurements from the imaging sensor [40].…”

“…The captured hyperspectral imagery had a ground sampling distance (GSD) ranging between 0.5 to 20 cm. The HSI system was characterized in our lab at RIT using a LabSphere Helios Integrating Sphere (LabSphere, North Sutton, NH, USA), which is coupled to an on-board calibrated spectrometer to determine a calibration of the Headwall system to convert the raw digital numbers (DN) to spectral radiance (Wm −2 nm −1 sr −1 ) [40]. The placement of Spectralon R (LabSphere, North Sutton, NH, USA) panels within the scene enabled the conversion of the imagery into surface reflectance.…”

“…Our enhanced approach, which is applicable to any remote sensing time series, demonstrated a retrieval of sediment filling factor that was consistent with nearby ground truth measurements [9]; however, in that earlier study, the available ground truth was not directly within the overlapping field of view of the multi-view, multi-temporal G-LiHT hyperspectral imagery used. In the present study, we address this shortcoming using multi-view, multi-temporal hyperspectral imagery acquired from a mast-mounted hyperspectral imaging (HSI) system [40] and contemporaneous ground truth collected by us during a field campaign at the Virginia Coast Reserve (VCR) [41] Long Term Ecological Research (LTER) [42] site in July 2018. In our present study, the ground truth that we collected provides a large number of validation points within the field of view, and we find good correlation in the retrieved sediment filling factor with the directly measured field sediment bulk density.…”

Collaborative Science to Enhance Coastal Resilience and Adaptation

“…Scientists and engineers apply techniques such as change detection analysis with time series of images to characterize the environment to support planning. Bachmann et al (2019) illustrated the use of hyperspectral imagery to improve coastal characterization and these approaches provide ocean observing systems with nearshore Digital Elevation Models and features from the land such as biomass and the water such as turbidity.…”