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WU Ze, MIAO Xiaodong, LI Weiwen, YU Hu. Low-Visibility Road Target Detection Algorithm Based on Infrared and Visible Light Fusion[J]. Infrared Technology , 2022, 44(11): 1154-1160.
Citation: WU Ze, MIAO Xiaodong, LI Weiwen, YU Hu. Low-Visibility Road Target Detection Algorithm Based on Infrared and Visible Light Fusion[J]. Infrared Technology , 2022, 44(11): 1154-1160.
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Low-Visibility Road Target Detection Algorithm Based on Infrared and Visible Light Fusion

  • School of Mechanical and Power Engineering, Nanjing Tech. University, Nanjing 211816, China

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  • Received Date: July 12, 2022
  • Revised Date: November 01, 2022
    Graphical Abstract
    • Abstract
  • Both infrared and visible images are widely used in the field of target detection; however, unimodal images find it difficult to satisfy the requirements of low-visibility road target detection. Therefore, this study proposes a low-visibility road target detection algorithm based on infrared-visible fusion from the perspective of bimodal fusion. First, the input images were pre-processed using various IR-visible dual-mode image fusion algorithms, five parameters, including mean, standard deviation, information entropy, mean gradient, and spatial frequency of the fused images, were quantitatively analyzed, and the detection model for low-visibility road targets was obtained by optimizing the training detection network. Finally, the accuracies of the algorithm and model were evaluated in terms of the model-training results and target detection results. The experimental results demonstrate that the false- and missed-detection rates of the model trained by the algorithm in this study were significantly reduced compared with other algorithms, and the detection accuracy was improved from 75.51% to 88.86% compared with the existing algorithm using unimodal images; in addition, the image processing speed satisfied the requirement for real-time detection.
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    • References (16)
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