HVUNet: hybrid vit-UNet for infrared dim and small target detection

Jinxin Guo; Weida Zhan; Yueyi Han; Jian Xing

doi:10.1117/12.3040436

10 September 2024 HVUNet: hybrid vit-UNet for infrared dim and small target detection

Jinxin Guo, Weida Zhan, Yueyi Han, Jian Xing

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Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132570P (2024) https://doi.org/10.1117/12.3040436
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

Based on the Visual Transformer (ViT), the infrared dim and small target detection is a pioneering task in the field of deep learning. Existing ViT methods applied in the Unet global network utilize a single attention mechanism for each layer of the network, directing the network's focus towards the regions of dim and small targets in the images. However, these methods neglect the correlation between the encoding and decoding paths of the Unet network, failing to fully exploit the powerful feature extraction capabilities of ViT. Consequently, there is a continuous increase in the false negative and false positive rates of dim and small target detection.This paper proposes an improvement to the Unet-type network by introducing a novel multi-level ViT dim and small target detection network—HVUNet. Specifically, we design low-level feature extraction residual blocks to extract low-level features from each level of the image. Furthermore, we introduce three types of multi-head attention modules in the encoding, decoding, and concatenation paths respectively, to capture the long-range dependencies of the three paths. This overcomes the challenge of significant differences in the distribution of background and target information in infrared dim and small target images.Experimental results on public datasets demonstrate that our HVUNet significantly reduces the false negative and false positive rates of small target detection, thereby improving detection probability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinxin Guo, Weida Zhan, Yueyi Han, and Jian Xing "HVUNet: hybrid vit-UNet for infrared dim and small target detection", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132570P (10 September 2024); https://doi.org/10.1117/12.3040436

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KEYWORDS

Small targets

Target detection

Infrared radiation

Matrices

Infrared imaging

Feature extraction

Infrared detectors

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