DU Nini, SHAN Kaidong, WEI Shasha. LPformer: Laplacian Pyramid Multi-Level Transformer for Infrared Small Target Detection[J]. Infrared Technology , 2023, 45(6): 630-638.
Citation: DU Nini, SHAN Kaidong, WEI Shasha. LPformer: Laplacian Pyramid Multi-Level Transformer for Infrared Small Target Detection[J]. Infrared Technology , 2023, 45(6): 630-638.

LPformer: Laplacian Pyramid Multi-Level Transformer for Infrared Small Target Detection

More Information
  • Received Date: January 16, 2023
  • Revised Date: January 31, 2023
  • Infrared small target detection refers to the segmentation of small targets from infrared images. This is of significance in the application of fire detection systems, maritime surveillance, and other rescue systems. However, because of factors such as small target size, inconspicuous features, and complex background environment, the detection performance of current infrared small target detection algorithms is generally limited. To address this issue, an infrared small target detection algorithm based on the Laplacian pyramid multi-level transformer (LPformer) was designed in this study. During network iteration, small infrared targets are prone to losing texture detail information owing to their small size. The Laplacian pyramid was used to extract different levels of high-frequency boundary information from the original input infrared image. A structural information conversion module was then fused with the features of different levels in the backbone network to compensate for the lost texture information. Next, to further improve the discriminative ability of the network and suppress the false alarm rate while improving the detection accuracy, a channel-based transformer structure that takes each channel feature map as tokens was also adopted. This calculated the self-attention map along the channel dimension. Experimental results demonstrated that the detection performance of the proposed algorithm was higher than that of current advanced detection algorithms.
  • [1]
    LI Z M, Mei L F, Song M. A survey on infrared weak small target detection method[C]//Advanced Materials Research, 2014, 945: 1558-1560.
    [2]
    贺顺, 谢永妮, 杨志伟, 等. 基于IHBF的增强局部对比度红外小目标检测方法[J]. 红外技术, 2022, 44(11): 1132-1138. http://hwjs.nvir.cn/article/id/0f2609dc-79df-467e-ac1d-4d5f888850d1

    HE Shun, XIE Yongni, YANG Zhiwei, et al. IHBF-based enhanced local contrast measure method for infrared small target detection[J]. Infrared Technology, 2022, 44(11): 1132-1138. http://hwjs.nvir.cn/article/id/0f2609dc-79df-467e-ac1d-4d5f888850d1
    [3]
    李飚, 徐智勇, 王琛, 等. 基于自适应梯度倒数滤波红外弱小目标场景背景抑制[J]. 光电工程, 2021, 48(8): 47-58. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC202108004.htm

    LI B, XU Z Y, WANG C, et al. Background suppression for infrared dim small target scene based on adaptive gradient reciprocal filtering[J]. Opto-Electron Eng. , 2021, 48(8): 47-58. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC202108004.htm
    [4]
    聂青凤, 刘应杰, 梁赟. 基于稀疏约束神经网络的红外弱小目标检测技术[J]. 电光与控制, 2022, 29(8): 40-44. https://www.cnki.com.cn/Article/CJFDTOTAL-DGKQ202208008.htm

    NEI Qingfeng, LIU Yingjie, LIANG Yun. Infrared dim target detection based on neural network model with sparsity constraint[J]. Electronics Optics & Control, 2022, 29(8): 40-44. https://www.cnki.com.cn/Article/CJFDTOTAL-DGKQ202208008.htm
    [5]
    BAI Xiangzhi, ZHOU Fugen. Analysis of new top-hat transformation and the application for infrared dim small target detection[J]. Pattern Recognition, 2010, 43(6): 2145-2156. DOI: 10.1016/j.patcog.2009.12.023
    [6]
    CL Philip CHEN, LI Hong, WEI Yantao, et al. A local contrast method for small infrared target detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 52(1): 574-581.
    [7]
    HAN Jinhui, Saed Moradi, Iman Faramarzi, et al. Infrared small target detection based on the weighted strengthened local contrast measure[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 18(9): 1670-1674.
    [8]
    HOU X, ZHANG L. Saliency detection: a spectral residual approach[C]//2007 IEEE Conference on Computer Vision and Pattern Recognition of IEEE, 2007: 1-8.
    [9]
    DAI Yimian, WU Yiquan. Reweighted infrared patch-tensor model with both nonlocal and local priors for single-frame small target detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2017, 10(8): 3752-3767. DOI: 10.1109/JSTARS.2017.2700023
    [10]
    GAO Chenqiang, MENG Deyu, YANG Yi, et al. Infrared patch-image model for small target detection in a single image[J]. IEEE Transactions on Image Processing, 2013, 22(12): 4996-5009. DOI: 10.1109/TIP.2013.2281420
    [11]
    ZHANG Landan, PENG Lingbing, ZHANG Tianfang, et al. Infrared small target detection via non-convex rank approximation minimization joint l2, 1 norm[J]. Remote Sensing, 2018, 10(11): 1821 DOI: 10.3390/rs10111821
    [12]
    ZHANG Landan, PENG Zhenming. Infrared small target detection based on partial sum of the tensor nuclear norm[J]. Remote Sensing, 2019, 11(4): 382. DOI: 10.3390/rs11040382
    [13]
    XU Yonghui, ZHANG J A. Real-time detection algorithm for small space targets based on max-median filter[J]. Journal of Information and Computational Science, 2014, 11(4): 1047-1055. DOI: 10.12733/ jics20102961.
    [14]
    谷雨, 张宏宇, 孙仕成. 融合多尺度分形注意力的红外小目标检测模型[J/OL]. 电子与信息学报: 1-10[2023-01-14]. http://kns.cnki.net/kcms/detail/11.4494.TN.20221107.0920.007.html.

    GU Yu, ZHANG Hongyu, SUN Shicheng. Infrared small target detection model with multi-scale fractal attention[J/OL]. Journal of Electronics & Information Technology: 1-10[2023-01-14]. http://kns.cnki.net/kcms/detail/11.4494.TN.20221107.0920.007.html
    [15]
    邵斌, 杨华, 朱斌, 等. 基于实时语义分割的红外小目标检测算法[J/OL]. 激光与光电子学进展: 1-15[2023-01-14]. http://kns.cnki.net/kcms/detail/31.1690.TN.20221031.1649.140.html.

    SHAO Bin, YANG Hua, ZHU Bing, et al. Infrared small target detection algorithm based on real-time semantic segmentation[J/OL]. Laser & Optoelectronics Progress: 1-15[2023-01-14]. http://kns.cnki.net/kcms/detail/31.1690.TN.20221031.1649.140.html
    [16]
    WANG Huan, ZHOU Luping, WANG Lei. Miss detection vs. false alarm: Adversarial learning for small object segmentation in infrared images[C]//Proceedings of 2019 IEEE/CVF International Conference on Computer Vision(ICCV), 2019: 8508-8517. DOI: http://dx.doi.org/10.1109/ICCV.2019.00860.
    [17]
    DAI Y, WU Y, ZHOU F, et al. Asymmetric contextual modulation for infrared small target detection[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021: 950-959.
    [18]
    LI Boyang, XIAO Chao, WANG Longguang, et al. Dense nested attention network for infrared small target detection[J]. IEEE Transactions on Image Processing, 2022: DOI: 10.1109/TIP.2022.3199107.
    [19]
    张传聪, 李范鸣, 饶俊民. 基于特征显著性融合的红外小目标检测[J]. 半导体光电, 2022, 43(4): 828-834. DOI:10.16818/j.issn1001-5868. 2022032901.

    ZHANG Chuancong, LI Fanming, RAO Junmin. Infrared small target detection based on feature saliency fusion[J]. Semiconductor Optoelectronics, 2022, 43(4): 828-834. DOI:10.16818/j.issn1001-5868. 2022032901.
    [20]
    王翔. 一种复杂海空背景下的红外小目标检测跟踪算法[J]. 光学与光电技术, 2022, 20(2): 113-119. DOI:10.19519/j.cnki.1672-3392. 2022.02.010.

    WANG Xiang. A detecting and tracking algorithm for the infrared small targets under the complex sea-sky background[J]. Optics & Optoelectronic Technology, 2022, 20(2): 113-119. DOI:10.19519/j.cnki.1672-3392. 2022.02.010.
    [21]
    薛锡瑞, 黄树彩, 马佳顺, 等. 基于局部熵参考预处理的RPCA红外小目标检测[J]. 红外技术, 2021, 43(7): 649-657. http://hwjs.nvir.cn/article/id/e8541151-1530-4561-ad38-42349b5da1b8

    XUE Xirui. HUANG Shucai, MA Jiashun, et al. RPCA infrared small target detection based on local Entropy reference in preprocessing[J]. Infrared Technology, 2021, 43(7): 649-657. http://hwjs.nvir.cn/article/id/e8541151-1530-4561-ad38-42349b5da1b8
    [22]
    朱硕雅, 杨德振, 贾鹏, 等. 时空联合红外小目标检测算法的设计与实现[J]. 激光与红外, 2021, 51(3): 388-392. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202103023.htm

    ZHU Shuoya, YANG Dezhen, JIA Peng, et al. Design and implementation of space-time combined infrared small target detection algorithm[J]. Laser and Infrared, 2021, 51(3): 388-392. https://www.cnki.com.cn/Article/CJFDTOTAL-JGHW202103023.htm
    [23]
    CHEN G, WANG W, TAN S. IRST Former: a hierarchical vision transformer for infrared small target detection[J]. Remote Sensing, 2022, 14(14): 3258.
    [24]
    高峰, 孟德森, 解正源, 等. 基于Transformer和动态3D卷积的多源遥感图像分类[J/OL]. 北京航空航天大学学报: 1-11[2023-01-14]. DOI: 10.13700/j.bh.1001-5965.2022.0397

    GAO Feng, MENG Desen, XIE Zhengyuan, et al. Multi-source remote sensing image joint classification based on transformer and dynamic 3D-convolution[J/OL]. Journal of Beijing University of Aeronautics and Astronautics: 1-11[2023-01-14] (DOI: 10.13700/j.bh.1001-5965.2022).
    [25]
    Jonnalagadda A, WANG W Y, Manjunath B S, et al. Foveater: foveated transformer for image classification[J/OL]. arXiv preprint arXiv: 2105.14173, (https://doi.org/10.48550/arXiv.2105.14173)
    [26]
    HAN K, XIAO A, WU E, et al. Transformer in transformer[J]. Advances in Neural Information Processing Systems, 2021, 34: 15908-15919.
    [27]
    Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on Medical image Computing and Computer-assisted Intervention, 2015: 234-241.
    [28]
    WANG X, YU K, DONG C, et al. Recovering realistic texture in image super-resolution by deep spatial feature transform[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018: 606-615.
    [29]
    DAI Y, WU Y, ZHOU F, et al. Attentional local contrast networks for infrared small target detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(11): 9813-9824.
    [30]
    HAN J, Moradi S, Faramarzi I, et al. Infrared small target detection based on the weighted strengthened local contrast measure[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 18(9): 1670-1674.
    [31]
    CHEN C L P, LI H, WEI Y, et al. A local contrast method for small infrared target detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 52(1): 574-581.
    [32]
    GAO C, MENG D, YANG Y, et al. Infrared patch-image model for small target detection in a single image[J]. IEEE Transactions on Image Processing, 2013, 22(12): 4996-5009.
    [33]
    ZHANG L, PENG L, ZHANG T, et al. Infrared small target detection via non-convex rank approximation minimization joint l2, 1 norm[J]. Remote Sensing, 2018, 10(11): 1821.
    [34]
    ZHANG L, PENG Z. Infrared small target detection based on partial sum of the tensor nuclear norm[J]. Remote Sensing, 2019, 11(4): 382.
    [35]
    SUN Y, YANG J, An W. Infrared dim and small target detection via multiple subspace learning and spatial-temporal patch-tensor model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 59(5): 3737-3752.
  • Related Articles

    [1]WANG Zhen, LIU Lei. Infrared Image Segmentation of Power Equipments Based on Improved Watershed Algorithm[J]. Infrared Technology , 2025, 47(4): 484-492.
    [2]XU Guangxian, ZHOU Weijie, MA Fei. Fusion of Hyperspectral and Multispectral Images Using a CNN Joint Multi-Scale Transformer[J]. Infrared Technology , 2025, 47(1): 52-62.
    [3]YUAN Hongchun, ZHANG Bo, CHENG Xin. Underwater Image Enhancement Algorithm Combining Transformer and Generative Adversarial Network[J]. Infrared Technology , 2024, 46(9): 975-983.
    [4]LI Qiuheng, DENG Hao, LIU Guihua, PANG Zhongxiang, TANG Xue, ZHAO Junqin, LU Mengyuan. Infrared and Visible Images Fusion Method Based on Multi-Scale Features and Multi-head Attention[J]. Infrared Technology , 2024, 46(7): 765-774.
    [5]DU Nini, SHAN Kaidong, WANG Jianchao. HRformer: Hierarchical Regression Transformer for Infrared Small-Target Detection[J]. Infrared Technology , 2024, 46(2): 199-207.
    [6]HU Chunan, WANG Fengqi, ZHU Donglin. Improved Sparrow Search Algorithm and Its Application in Infrared Image Segmentation[J]. Infrared Technology , 2023, 45(6): 605-612.
    [7]LIU He, ZHAO Tiancheng, LIU Junbo, JIAO Lixin, XU Zhihao, YUAN Xiaocui. Deep Residual UNet Network-based Infrared Image Segmentation Method for Electrical Equipment[J]. Infrared Technology , 2022, 44(12): 1351-1357.
    [8]ZHANG Lijuan, MEI Chang, LI Chaoran, ZHANG Run. Retinal Vessel Image Segmentation Based on RAU-net[J]. Infrared Technology , 2021, 43(12): 1222-1227,1233.
    [9]ZHANG Lian, LI Mengtian, YU Songlin, GONG Yu, YANG Hongjie. An Infrared Image Segmentation Method Based on Improved Lazy Snapping Algorithm[J]. Infrared Technology , 2021, 43(4): 372-377.
    [10]WANG Liebing, JIANG Xiongfei, SHI Chunguang, LI Huichong, MA Xiaolong. Infrared Small Target Detection Based on Image Filtering and Hough Transform[J]. Infrared Technology , 2020, 42(7): 683-687.
  • Cited by

    Periodical cited type(3)

    1. 刘祺,曹林,田澍,杜康宁,宋沛然,郭亚男. 用于遥感图像变化检测的结构感知多尺度混合网络. 激光与光电子学进展. 2024(14): 323-333 .
    2. 闵锋,刘彪,况永刚,毛一新,刘煜晖. 基于空间自适应和内容感知的红外小目标检测. 红外技术. 2024(07): 735-742 . 本站查看
    3. 陈怡馨,马曾. 无线网络信息差分隐私的动态可搜索加密仿真. 计算机仿真. 2024(10): 424-427+442 .

    Other cited types(4)

Catalog

    Article views (280) PDF downloads (68) Cited by(7)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return