Absorption-Feature-Guided Distance-Decoupled Estimation and Band Selection for LWIR Hyperspectral Passive Ranging

2026-06-30

AI Summary

This work addresses the ill-posed and computationally expensive nature of long-wave infrared hyperspectral passive ranging, which arises from the nonlinear coupling among atmospheric absorption, target temperature, emissivity, and path radiance. The authors propose the ADER framework, which explicitly leverages atmospheric absorption structures—particularly ozone features—to decouple distance estimation. By modeling emissivity with a B-spline smoothness prior and employing ozone-absorption-guided pixel classification, the method first obtains an initial range estimate via one-dimensional absorption residual minimization and subsequently refines it using a full radiative transfer model. A greedy band selection strategy based on multi-scenario effective Fisher information further enhances efficiency. Evaluated on real-world scenes, the approach recovers depth structures consistent with LiDAR measurements, achieving superior ranging accuracy and approximately two orders of magnitude faster computation than existing methods.

Abstract

Long-wave infrared (LWIR) hyperspectral observations contain distance-dependent atmospheric absorption signatures, providing a physical basis for long-range passive ranging. However, in natural scenes, these signatures are nonlinearly coupled with target temperature, material emissivity, and path radiance, making distance inversion from observed radiance ill posed. Existing methods typically rely on full-band measurements and pixel-wise joint optimization, which is computationally expensive and does not explicitly exploit sharp atmospheric absorption structures. This paper proposes an Absorption-Guided Distance-Decoupled Estimation and Refinement (ADER) framework for LWIR hyperspectral passive ranging. ADER represents emissivity with B-spline control points under a smoothness prior, suppressing overfitting to atmospheric absorption structures and enabling distance-decoupled estimation. It further uses ozone-absorption cues to classify pixels into emission-dominant and reflection-dominant groups. For emission-dominant pixels, ADER compensates path radiance and transmittance and estimates distance by one-dimensional absorption-residual minimization. For reflection-dominant pixels, ADER refines the initial estimate using downwelling-radiance compensation based on the complete radiative model. To reduce spectral redundancy, ADER also introduces a greedy band selection strategy based on multi-scene effective Fisher information for the distance parameter. Experiments on real scenes show that ADER recovers LiDAR-consistent spatial distance structures under both full-band and 20-band settings, improves ranging accuracy in the evaluated regions, and achieves approximately two orders of magnitude speedup over a public full-band hyperspectral ranging method.

Problem

• LWIR hyperspectral
• passive ranging
• atmospheric absorption
• distance inversion
• ill-posed problem

Innovation

• distance-decoupled estimation
• absorption-feature guidance
• emissivity modeling
• band selection
• LWIR hyperspectral ranging