Multiscale-Superpixel-Based SparseCEM for Hyperspectral Target Detection

被引:12
|
作者
Yang, Xiaoli [1 ,2 ]
Zhao, Min [1 ]
Gao, Tiande [1 ]
Chen, Jie [1 ]
Zhang, Jie [3 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Peoples R China
[2] Xian Aeronaut Univ, Sch Elect Engn, Xian 710077, Peoples R China
[3] Shanghai Shengyao Intelligent Technol Co Ltd, Shanghai 200000, Peoples R China
关键词
Detectors; Object detection; Hyperspectral imaging; Task analysis; Correlation; Tensors; Shape; Constrained energy minimization (CEM); hyperspectral target detection; multiscale; object level; superpixel;
D O I
10.1109/LGRS.2021.3079445
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Jointly exploiting spectral information and spatial information, rather than working on individual pixels, is important for hyperspectral target detection. In this letter, we propose a hyperspectral target detection method relying on superpixel structures of the input image. Multiscale superpixels are generated to capture textures of the image, and each superpixel is summarized to its representative, which is the average of all its pixels. The SparseCEM detector is then applied to these representatives. Finally, the detection results from all scales are fused to achieve the final output. Our experiment results show that the multiscale-superpixel-based SparseCEM detector (MSSD) outperforms the compared typical detection methods.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] SUPERPIXEL BASED HYPERSPECTRAL TARGET DETECTION
    Caliskan, Akin
    Bati, Emrecan
    Koz, Alper
    Alatan, A. Aydin
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 7010 - 7013
  • [2] SparseCEM and SparseACE for Hyperspectral Image Target Detection
    Yang, Shuo
    Shi, Zhenwei
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2014, 11 (12) : 2135 - 2139
  • [3] SPATIALLY REGULARZIED SPARSECEM FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES
    Yang, Xiaoli
    Li, Zeng
    Chen, Jie
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 2765 - 2768
  • [4] Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion
    Liu, Ming
    Chen, Shichao
    Lu, Fugang
    Xing, Mengdao
    Wei, Jingbiao
    [J]. SENSORS, 2021, 21 (05) : 1 - 15
  • [5] Multiscale Superpixel Guided Discriminative Forest for Hyperspectral Anomaly Detection
    Cheng, Xi
    Zhang, Min
    Lin, Sheng
    Zhou, Kexue
    Wang, Liang
    Wang, Hai
    [J]. REMOTE SENSING, 2022, 14 (19)
  • [6] Superpixel sparse representation for target detection in hyperspectral imagery
    Dong, Chunhua
    Naghedolfeizi, Masoud
    Aberra, Dawit
    Qiu, Hao
    Zeng, Xiangyan
    [J]. COMPRESSIVE SENSING VI: FROM DIVERSE MODALITIES TO BIG DATA ANALYTICS, 2017, 10211
  • [7] Multiscale Superpixel-Based Active Learning for Hyperspectral Image Classification
    Lu, Qikai
    Wei, Lifei
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [8] Multiscale superpixel-based fusion framework for hyperspectral image classification
    Jia, Sen
    Deng, Xianglong
    Wu, Kuilin
    [J]. 2018 FIFTH INTERNATIONAL WORKSHOP ON EARTH OBSERVATION AND REMOTE SENSING APPLICATIONS (EORSA), 2018, : 448 - 452
  • [9] Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification
    Zhang, Shuzhen
    Li, Shutao
    Fu, Wei
    Fang, Leiyuan
    [J]. REMOTE SENSING, 2017, 9 (02)
  • [10] SUBPIXEL TARGET DETECTION IN HYPERSPECTRAL IMAGES FROM SUPERPIXEL BACKGROUND STATISTICS
    Liang, Yilong
    Markopoulos, Panos P.
    Saber, Eli S.
    [J]. 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 7018 - 7021