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IRPol-Fuse: Energy-structure coordination for infrared polarization fusion under low visibility

arXiv 2608.07848 ↗First posted 8 Aug 2026cs.CVcited by 0

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Abstract (arXiv)

Robust perception under low-visibility conditions requires fused imagery that jointly preserves infrared thermal saliency and polarization-derived structural details. However, existing infrared-polarization image fusion (IPIF) methods often overemphasize dominant infrared responses, causing weak yet informative polarization textures in dark regions to be suppressed. To address this issue, we propose IRPol-Fuse, an energy-structure coordinated IPIF framework for challenging low-visibility scenarios. The proposed framework contains three key modules: Polarization Attention Fusion for adaptive infrared-polarization allocation, Infrared Highlight Injector for highlight-guided infrared preservation, and Polarization Texture Injector for polarization texture restoration and fine-detail recovery. We further construct LI-PI, a dedicated infrared-polarization evaluation dataset for low-visibility and visually concealed scenes. Experiments on LI-PI and the public LDDRS dataset demonstrate that IRPol-Fuse achieves favorable performance in thermal target preservation, structural detail recovery, and visual naturalness. Region-aware evaluation and downstream object detection further verify that the proposed energy-structure coordination strategy effectively preserves both infrared target saliency and polarization-derived structural information. Code is available at https://github.com/1hzf/IRPolar-Fuse .

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 36 references that are in the map. First posted on arXiv 8 Aug 2026.

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5 of 36 references.

References · 5

  1. 2022CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusioncited by 223
  2. 2024FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mambacited by 81
  3. 2025LUT-Fuse: Towards Extremely Fast Infrared and Visible Image Fusion via Distillation to Learnable Look-Up Tablescited by 9
  4. 2021Deep Snapshot HDR Reconstruction Based on the Polarization Cameracited by 7
  5. 2025FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolutioncited by 3

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