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Infrared small target detection based on the combination of single image super-resolution reconstruction and YOLOX

Published: 29 May 2023 Publication History

Abstract

For the infrared search and tracking system, it is necessary to increase the ability to detect small infrared targets against complex backgrounds. YOLOX is a high-performance detector, but its detection performance is constrained when it uses data from low-resolution infrared images with small targets. However, occasionally design constraints and budgetary restraints will prevent the optical system and sensor resolution from being increased enough to improve image quality. Real-ESRGAN is used to solve this issue by reconstructing a high-resolution infrared image from its low-resolution counterpart, which will be used as YOLOX-S's input. Also, the YOLOX-S training strategy is modified further to make it appropriate for the detection of infrared small targets, including the Mosaic and MixUp data augmentation and the size of ground-truth. The average precision achieved by the suggested method in this work increases from 63.70% to 77.19%, which shows a considerable improvement in infrared small target detection when compared with the original model by inputting original images.

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Cited By

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  • (2025)Recognition of UAVs in Infrared Images Based on YOLOv8IEEE Access10.1109/ACCESS.2024.350058313(1534-1545)Online publication date: 2025
  • (2024)CS-ViG-UNet: Infrared small and dim target detection based on cycle shift vision graph convolution networkExpert Systems with Applications10.1016/j.eswa.2024.124385254(124385)Online publication date: Nov-2024
  • (2023)Learning Shape-Biased Representations for Infrared Small Target DetectionIEEE Transactions on Multimedia10.1109/TMM.2023.332574326(4681-4692)Online publication date: 20-Oct-2023

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  1. Infrared small target detection based on the combination of single image super-resolution reconstruction and YOLOX

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    CACML '23: Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning
    March 2023
    598 pages
    ISBN:9781450399449
    DOI:10.1145/3590003
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 29 May 2023

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    View all
    • (2025)Recognition of UAVs in Infrared Images Based on YOLOv8IEEE Access10.1109/ACCESS.2024.350058313(1534-1545)Online publication date: 2025
    • (2024)CS-ViG-UNet: Infrared small and dim target detection based on cycle shift vision graph convolution networkExpert Systems with Applications10.1016/j.eswa.2024.124385254(124385)Online publication date: Nov-2024
    • (2023)Learning Shape-Biased Representations for Infrared Small Target DetectionIEEE Transactions on Multimedia10.1109/TMM.2023.332574326(4681-4692)Online publication date: 20-Oct-2023

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