本文選題：高光譜　切入點：異常檢測　出處：《光子學報》2017年04期 　論文類型：期刊論文

【摘要】：針對基于逐像元處理的因果實時異常(Causal Real-time Relationship Reed-X Detector,CR-RRXD)檢測算法計算量大,以及基于逐像元方式邊檢測邊成像顯示的時間過長而不能滿足快速處理要求的缺陷,提出了一種基于逐行處理的CR-R-RXD檢測算法.與基于逐像元處理的CR-R-RXD檢測算法相比,該方法將高光譜圖像整行像元向量作為輸入,即處理一行高光譜數(shù)據(jù)只需計算一次,極大地減少了計算次數(shù).實驗結(jié)果表明,與R-RXD和基于逐像元處理的CR-R-RXD算法相比,本文算法可在獲得與R-RXD算法幾乎相同的檢測準確度的情況下,實現(xiàn)快速實時處理,其檢測準確度相較于基于逐像元處理的CR-R-RXD算法有所提高,且算法檢測時間大大縮短,增強了算法的時效性.
[Abstract]:The algorithm of causality Real-time Relationship Reed-X detector CR-RRXD based on pixel by pixel processing is computationally large, and the time of image display while detecting edge by pixel is too long to meet the requirement of fast processing. A new CR-R-RXD detection algorithm based on line by line processing is proposed. Compared with the CR-R-RXD detection algorithm based on pixel processing, the whole line pixel vector of hyperspectral image is used as input, that is to say, only one calculation is needed to process a row of hyperspectral data. The experimental results show that compared with R-RXD and CR-R-RXD algorithm based on pixel processing, the proposed algorithm can achieve fast real-time processing with almost the same detection accuracy as R-RXD algorithm. Compared with the CR-R-RXD algorithm based on pixel processing, the detection accuracy of the algorithm is improved, and the detection time of the algorithm is greatly shortened, which enhances the timeliness of the algorithm.
【作者單位】： 中國農(nóng)業(yè)大學信息與電氣工程學院;
【基金】：國家自然科學基金(Nos.61201415,61571170)資助~~
【分類號】：TP751
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本文編號：1631267