J4 ›› 2009, Vol. 36 ›› Issue (3): 512-516.

• 研究论文 • 上一篇    下一篇



  1. (西安电子科技大学 技术物理学院,陕西 西安  710071)
  • 收稿日期:2008-02-28 修回日期:2008-03-31 出版日期:2009-06-20 发布日期:2009-07-04
  • 通讯作者: 刘德连
  • 基金资助:


Hyperspectral subpixel target detection approach based on expectation-maximization cluster

LIU De-lian;WANG Bo;ZHANG Jian-qi   

  1. (School of Technical Physics, Xidian Univ., Xi'an  710071, China)
  • Received:2008-02-28 Revised:2008-03-31 Online:2009-06-20 Published:2009-07-04
  • Contact: LIU De-lian



关键词: 遥感, 高光谱, 亚像素目标, 目标检测, 图像分割


Background is a key interferene in target detection. To avoid the interferene of complex background, an expectation-maximization cluster based approach to subpixel detection in hyperspectral is presented that incorporates background segmentation to model complex background. First, the expectation-maximization cluster model is employed to segment whole background into homogenous regions. Then the adaptive matched subspace detection algorithm (AMSD) is applied in each homogenous region. Since the segmented regions are more homogenous than the whole complex background, our new approach can have a better performance. Experimental result with a real hyperspectral image has proved the validity of the new approach.

Key words: remote sensing, hyperspectral, subpixel target, target detector, image segmentation


  • TN219