Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurements

Published

February 6, 2025

Author(s)

Unay Dorken Gallastegi, Hoover Rueda-Chacón, Martin Stevens, Vivek Goyal

Abstract

Passive hyperspectral long-wave infrared measurements are remarkably informative about the surroundings, such as remote object material composition, temperature, and range; and air temperature and gas concentrations. Remote object material and temperature determine the spectrum of thermal radiance, and range, air temperature, and gas concentrations determine how this spectrum is modified by propagation to the sensor. We computationally separate these phenomena, introducing a novel passive range imaging method based on atmospheric absorption of ambient thermal radiance. Previously demonstrated passive absorption-based ranging methods assume hot and highly emitting objects. However, the temperature variation in natural scenes is usually low, making range imaging challenging. Our method benefits from explicit consideration of air emission and parametric modeling of atmospheric absorption. To mitigate noise in low-contrast scenarios, we jointly estimate range and intrinsic object properties by exploiting a variety of absorption lines spread over the infrared spectrum. Along with Monte Carlo simulations that demonstrate the importance of regularization, temperature differentials, and availability of many spectral bands, we apply this method to long-wave infrared (8–13 μm) hyperspectral image data acquired from natural scenes with no active illumination. Range features from 15 m to 150 m are recovered, with good qualitative match to unaligned lidar data.

Citation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volume

47

Issue

5

Pub Type

Journals

Download Paper

https://doi.org/10.1109/TPAMI.2025.3538711

Local Download

Keywords

Absorption spectrum, black-body radiation, depth estimation, hyperspectral imaging, thermal radiation

Citation

Dorken Gallastegi, U. , Rueda-Chacon, H. , Stevens, M. and Goyal, V. (2025), Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurements, IEEE Transactions on Pattern Analysis and Machine Intelligence, [online], https://doi.org/10.1109/TPAMI.2025.3538711, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936781 (Accessed July 4, 2025)