DDCU-Net: dual dynamic convolutional U-Net for infrared small-target detection

Yi Zhang; Yan Zhang; Yu Han Zhong; Cheng Yu Li; Jiang Fan Zhang

doi:10.1117/12.3017712

15 December 2023 DDCU-Net: dual dynamic convolutional U-Net for infrared small-target detection

Yi Zhang, Yan Zhang, Yu Han Zhong, Cheng Yu Li, Jiang Fan Zhang

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710E (2023) https://doi.org/10.1117/12.3017712
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

Infrared small target detection has extensive applications in military reconnaissance, precision guidance, and urban security. To address the issues of limited pixel coverage, feature obliteration caused by the lack of texture and color, as well as poor generalization, we propose a dual dynamic convolution U-Net model: DDCU-Net. DDCU-Net not only incorporates the perception and downsampling of traditional dynamic convolution in the network to enhance target feature extraction capabilities, achieving more accurate shape segmentation, but also introduces a novel dynamic parameter convolutional kernel module at the network's skip connections and cross-layer fusion. This convolutional kernel parameter adapts locally to input instances, yielding a better fit for non-stationary infrared small targets and effectively improving network generalization. Experimental results on the two public datasets demonstrate the effectiveness of DDCU-Net's modules, outperforming other advanced algorithms in terms of detection accuracy and shape segmentation performance.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yi Zhang, Yan Zhang, Yu Han Zhong, Cheng Yu Li, and Jiang Fan Zhang "DDCU-Net: dual dynamic convolutional U-Net for infrared small-target detection", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710E (15 December 2023); https://doi.org/10.1117/12.3017712

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KEYWORDS

Target detection

Convolution

Infrared radiation

Infrared detectors

Small targets

Education and training

Feature extraction

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