An anomaly detection algorithm for hyperspectral imagery based on graph Laplacian

2020 ◽  
Author(s):  
Yuquan Gan ◽  
Ying Liu ◽  
Fanchao Yang
Keyword(s):  
Anomaly Detection ◽  
Hyperspectral Imagery ◽  
Graph Laplacian ◽  
Detection Algorithm

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

2017 ◽  
Vol 46 (4) ◽  
pp. 410003 ◽  
Author(s):  
付立婷 FU Li-ting ◽  
邓河 DENG He ◽  
刘春红 LIU Chun-hong
Keyword(s):  
Anomaly Detection ◽  
Hyperspectral Imagery ◽  
Detection Algorithm ◽  
On Line

Anomaly detection algorithm for hyperspectral imagery based on summation of spectral angles

2013 ◽  
Vol 6 (3) ◽  
pp. 325-331
Author(s):  
杜小平 DU Xiao-ping ◽  
刘明 LIU Ming ◽  
夏鲁瑞 XIA Lu-rui ◽  
陈杭 CHEN Hang
Keyword(s):  
Anomaly Detection ◽  
Hyperspectral Imagery ◽  
Detection Algorithm

Anomaly Detection in Hyperspectral Imagery Based on Spectral Gradient and LLE

2011 ◽  
Vol 121-126 ◽  
pp. 720-724
Author(s):  
Liang Liang Wang ◽  
Zhi Yong Li ◽  
Ji Xiang Sun
Keyword(s):  
Anomaly Detection ◽  
Euclidean Distance ◽  
Hyperspectral Imagery ◽  
Detection Algorithm ◽  
Hyperspectral Data ◽  
Experimental Results ◽  
Feature Analysis ◽  
Detection Problem ◽  
Local Linear Embedding ◽  
Linear Embedding

The local linear embedding algorithm(LLE) is applied into the anomaly detection algorithm on the basis of the feature analysis of the hyperspectral data. Then, to deal with the problem of declining capacity of identifying the neighborhood caused by the Euclidean distance, an improved LLE algorithm is developed. The improved LLE algorithm selects neighborhood pixels according to the spectral gradient, thus making the anomaly detection more robust to the changes of light and terrain. Experimental results prove the feasibility of using LLE algorithm to solve the anomaly detection problem, and the effectiveness of the algorithm in improving the detection performance.

Robust Background Subspace Based Anomaly Detection Algorithm for Hyperspectral Imagery

2010 ◽  
Vol 39 (12) ◽  
pp. 2224-2228
Author(s):  
蒲晓丰 PU Xiao-feng ◽  
雷武虎 LEI Wu-hu ◽  
黄涛 HUANG Tao ◽  
王迪 WANG Di
Keyword(s):  
Anomaly Detection ◽  
Hyperspectral Imagery ◽  
Detection Algorithm
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