Computer Science ›› 2018, Vol. 45 ›› Issue (6): 259-264.doi: 10.11896/j.issn.1002-137X.2018.06.046

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Real-time Sub-pixel Object Detection for Hyperspectral Image Based on Pixel-by-pixel Processing

LIN Wei-jun1, ZHAO Liao-ying1, LI Xiao-run2   

  1. School of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou 310018,China1;
    College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China2
  • Received:2017-04-12 Online:2018-06-15 Published:2018-07-24

Abstract: Sub-pixel target detection is one of the key technologies in the applications of hyperspectral images.Since the high dimensions of hyperspectral data increase apparently the storage space and complexity of data processing,real-time processing has become a crucial problem for target detection.Adaptive matched filter (AMF) is an effective algorithm for sub-pixel target detection.This paper derived the real-time AMF target detection procedure of hyperspectral images by using AMF as the sub-pixel target detection algorithm,based on the realization of real-time inversing of hyperspectral data’s covariance matrix with the pixel-by-pixel format transmission and storage by using Woodbury lemma.Expe-riments were conducted on synthetic data and real hyperspectral images.The results demonstrate that compared with non-real time AMF,real-time AMF needs less storage space and can achieve the same or slightly better detection accuracy.

Key words: Hyperspectral image processing, Pixel-by-pixel processing, Sub-pixel target detection, Causal processing, Adaptive matched filter

CLC Number: 

  • TP391
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