Universal computational thermal imaging overcoming the ghosting effect

2026-04-01

AI Summary

Thermal imaging in scenes with heterogeneous materials is prone to ghosting artifacts, which degrade texture details and significantly impair nighttime visual quality. To address this challenge, this work proposes TAG, a general-purpose computational thermal imaging framework that integrates hyperspectral photon flux with a non-parametric texture recovery algorithm to effectively suppress ghosting without requiring material priors. The method overcomes the key limitation of existing HADAR techniques, which are restricted to homogeneous materials, and achieves high-fidelity thermal imaging for general heterogeneous scenes for the first time. Notably, TAG successfully recovers facial expression textures, enabling cross-day-night facial emotion recognition and facilitating three-dimensional topological alignment under thermal imaging conditions.

Abstract

Thermal imaging is crucial for night vision but fundamentally hampered by the ghosting effect, a loss of detailed texture in cluttered photon streams. While conventional ghosting mitigation has relied on data post-processing, the recent breakthrough in heat-assisted detection and ranging (HADAR) opens a promising frontier for hyperspectral computational thermal imaging that produces night vision with day-like visibility. However, universal anti-ghosting imaging remains elusive, as state-of-the-art HADAR applies only to limited scenes with uniform materials, whereas material non-uniformity is ubiquitous in the real world. Here, we propose a universal computational thermal imaging framework, TAG (thermal anti-ghosting), to address material non-uniformity and overcome ghosting for high-fidelity night vision. TAG takes hyperspectral photon streams for nonparametric texture recovery, enabling our experimental demonstration of unprecedented expression recovery in thus-far-elusive ghostly human faces -- the archetypal, long-recognized ghosting phenomenon. Strikingly, TAG not only universally outperforms HADAR across various scenes, but also reveals the influence of material non-uniformity, shedding light on HADAR's effectiveness boundary. We extensively test facial texture and expression recovery across day and night, and demonstrate, for the first time, thermal 3D topological alignment and mood detection. This work establishes a universal foundation for high-fidelity computational night vision, with potential applications in autonomous navigation, reconnaissance, healthcare, and wildlife monitoring.

Problem

• thermal imaging
• ghosting effect
• material non-uniformity
• night vision
• hyperspectral imaging

Innovation

• thermal anti-ghosting
• computational thermal imaging
• hyperspectral photon streams
• material non-uniformity
• HADAR