Acta Photonica Sinica, Volume. 46, Issue 4, 410003(2017)

Fast Anomaly Detection Algorithm for Hyperspectral Imagery Based on Line-by-line Processing

FU Li-ting*, DENG He, and LIU Chun-hong
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    The Causal Real-time Relationship Reed-X Detector (CR-R-RXD) detecting algorithm based on the pixel-by-pixel processing for hyperspectral imagery, which has the problems of a large amount of computation, a long display time and a slow running speed. A CR-R-RXD detecting algorithm based on line by line was proposed in this paper. Compared with the CR-R-RXD method based on pixel by pixel processing, the whole row pixel vector of hyperspectral image was used as input in this proposed method. That is, dealing with a row of hyperspectral data needs to be calculated only once, which greatly reduces the calculation times. Experimental results show that, to compare with the R-RXD algorithm and CR-R-RXD method based on pixel by pixel processing, the proposed algorithm can achieve the process of fast real-time processing with almost the same accuracy as the R-RXD algorithm, the detection accuracy is improved to compare with the CR-R-RXD algorithm based on pixel by pixel processing, and the testing time of the algorithm is reduced, which enhances the timeliness of the algorithm.

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    FU Li-ting, DENG He, LIU Chun-hong. Fast Anomaly Detection Algorithm for Hyperspectral Imagery Based on Line-by-line Processing[J]. Acta Photonica Sinica, 2017, 46(4): 410003

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    Paper Information

    Received: Oct. 25, 2016

    Accepted: --

    Published Online: May. 3, 2017

    The Author Email: Li-ting FU (302691392@qq.com)

    DOI:10.3788/gzxb20174604.0410003

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