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Research on Channel-Wise Preprocessing for Enhanced Infrared Object Detection

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(11), pp.153-161
  • DOI : 10.9708/jksci.2024.29.11.153
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : October 17, 2024
  • Accepted : November 20, 2024
  • Published : November 29, 2024

Jae-Uk Kim 1,  Byung-In Choi 1

1한화시스템

Accredited

ABSTRACT

In this paper, we address the limitation of single-channel infrared (IR) images, which are difficult to directly apply to RGB-based detection models. Previously, a single channel was often replicated into three channels; however, this approach may limit detection performance due to information redundancy. To overcome this limitation, we propose a method that replicates the single-channel IR image into three channels, with each channel processed using different preprocessing techniques, such as CLAHE (Contrast Limited Adaptive Histogram Equalization), Laplacian Filter, and Top-hat transform, to improve detection performance. In this study, we utilized the RT-DETRv2 detection model and the Anti-UAV300 dataset, using IR images sampled at 10-frame intervals for our experiments. By evaluating the effects of each preprocessing technique and deriving the optimal configuration, our method achieved a 2.2% improvement in mean Average Precision (mAP) over conventional methods. This confirms that our method enhances performance over simple replication, presenting a novel approach to improving object detection performance in IR imaging, with promising applications across various fields, particularly in disaster situations where infrared cameras are utilized, as well as in nighttime surveillance and reconnaissance.

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