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RSS FeedsRemote Sensing, Vol. 12, Pages 697: Angle Distance-Based Hierarchical Background Separation Method for Hyperspectral Imagery Target Detection (Remote Sensing)

 
 

20 february 2020 18:01:40

 
Remote Sensing, Vol. 12, Pages 697: Angle Distance-Based Hierarchical Background Separation Method for Hyperspectral Imagery Target Detection (Remote Sensing)
 


Traditional detectors for hyperspectral imagery (HSI) target detection (TD) output the result after processing the HSI only once. However, using the prior target information only once is not sufficient, as it causes the inaccuracy of target extraction or the unclean separation of the background. In this paper, the target pixels are located by a hierarchical background separation method, which explores the relationship between the target and the background for making better use of the prior target information more than one time. In each layer, there is an angle distance (AD) between each pixel spectrum in HSI and the given prior target spectrum. The AD between the prior target spectrum and candidate target ones is smaller than that of the background pixels. The AD metric is utilized to adjust the values of pixels in each layer to gradually increase the separability of the background and the target. For making better discrimination, the AD is calculated through the whitened data rather than the original data. Besides, an elegant and ingenious smoothing processing operation is employed to mitigate the influence of spectral variability, which is beneficial for the detection accuracy. The experimental results of three real hyperspectral images show that the proposed method outperforms other classical and recently proposed HSI target detection algorithms.


 
187 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 12, Pages 698: A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network (Remote Sensing)
Remote Sensing, Vol. 12, Pages 696: Area-Based Dense Image Matching with Subpixel Accuracy for Remote Sensing Applications: Practical Analysis and Comparative Study (Remote Sensing)
 
 
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