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Early versus Late RGB-Infrared Fusion for Counter-UAV Detection: A Comparative Study

Alberto De Zan, Denis Tavaris, Gian Luca Foresti, Ivan Scagnetto · 2026 · arXiv

DOI: 10.48550/arXiv.2610.29828 · open-access PDF

German

In diesem Papier wird eine neue Strategie für die Erkennung von UAVs durch Sichtbare (RGB) und Infrarot (IR) Fusion vorgestellt, um Genauigkeit und Präzision in harten Umgebungen und Wetterbedingungen zu verbessern. In dieser Forschung wurden zwei entgegengesetzte Ansätze untersucht und umgesetzt: Die erste betrifft Bildebene (early) Fusion, die zwei verschiedene Spektren in ein einziges Bild fusioniert, auf das ein Detektor angewendet wird.

Machine translation (Meta M2M100); the English original follows.

Abstract

This paper presents a novel strategy for UAV detection through visible (RGB) and infrared (IR) fusion, in order to improve accuracy and precision in harsh environments and weather conditions. In this research, two opposite approaches have been studied and implemented: the first concerns image-level (early) fusion, which merges two different spectra into a single image to which one detector is applied. On the other hand, the second approach, called decision-level (late) fusion, focuses on blending together the output bounding boxes of two different detection pipelines, aiming to create a common

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