• Electronics Optics & Control
  • Vol. 24, Issue 7, 37 (2017)
LIAO Jia-jun, LIU Zhi-gang, and JIANG Jiang-jun
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2017.07.008 Cite this Article
    LIAO Jia-jun, LIU Zhi-gang, JIANG Jiang-jun. Sparse Representation Algorithm with Improved Bilateral Filtering for Hyperspectral Image Target Detection[J]. Electronics Optics & Control, 2017, 24(7): 37 Copy Citation Text show less

    Abstract

    In order to make full use of the spatial information contained in the hyperspectral image,an improved bilateral filtering is applied to the target detection,and a bilateral filtering algorithm based on spectral angle matching for sparse representation of hyperspectral target detection is proposed.By combining the spectral angle matching with the bilateral filtering,the similarity between the pixels of hyperspectral image is used as the weight of bilateral filtering.The noise in the band is suppressed and the target is highlighted.Then the target detection is carried out by sparse representation algorithm.Experimental results show that:Compared with the traditional sparse representation method and the sparse representation algorithm with normal bilateral filtering,the proposed method has better detection performance.It is proved that making full use of the spatial information of hyperspectral images can further improve the target detection results.
    LIAO Jia-jun, LIU Zhi-gang, JIANG Jiang-jun. Sparse Representation Algorithm with Improved Bilateral Filtering for Hyperspectral Image Target Detection[J]. Electronics Optics & Control, 2017, 24(7): 37
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