[an error occurred while processing this directive]
   
 
���¿��ټ��� �߼�����
   ��ҳ  �ڿ�����  ��ί��  Ͷ��ָ��  �ڿ�����  ��������  �� �� ��  ��ϵ����
�������պ����ѧѧ�� 2009, Vol. 35 Issue (3) :342-346    DOI:
���� ����Ŀ¼ | ����Ŀ¼ | ������� | �߼����� << | >>
����ͶӰѰ�ٵĸ߹���ͼ���쳣��Ⲣ���㷨
�� ά, �Ի۽�, �� ��*
�������պ����ѧ ������ѧ���繤��ѧԺ, ���� 100191
Parallel algorithm of anomalies detection in hyperspectral image with projection pursuit
Wang Wei, Zhao Huijie, Dong Chao*
School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

ժҪ
�����
�������
Download: PDF (0KB)   HTML 1KB   Export: BibTeX or EndNote (RIS)      Supporting Info
ժҪ ͶӰѰ�ٷ�������Ч��ȡ�����еķǸ�˹�ṹ͹���쳣��Ϣ,�����������ͶӰ����ʱ���ڼ�����������ʱ�䳤������,Ϊ��ߴ���Ч��,���һ�ֻ�Ⱥ�����µIJ����㷨.ѡ��ƫ�Ⱥͷ�������ΪͶӰָ��,���������ع�����Ϊ�ض�ͶӰ������������,�������ͶӰ����.�ڲ��м������ѡ����ͶӰָ��ʱ,�ָ�ͼ�����ݷֲ��洢�ڸ���Ⱥ���,�����ӿ鳯��ѡ������ͶӰ��,��ָ�����ʽ���ηֽ�,ʹ�������ָ�����������������ݾ�Ϊ��������,������ݾֲ�������,������һ��"��������"�Ļ�������㷨���ؾ���̶�.����ʵ����ģ�黯�߹����������ڻ�Ⱥϵͳ�Ͻ��в���,�ﵽ�˽Ϻõļ���Ч��,�����ò����㷨�������õIJ�������.
Service
�ѱ����Ƽ�������
�����ҵ����
�������ù�����
Email Alert
RSS
�����������
��ά
�Ի۽�
����
�ؼ����� ң��   ͼ���쳣���   �����㷨   ͶӰѰ��   �ض�ͶӰ����     
Abstract�� Projection pursiut can extract non-Gaussian structure in hyperspectral data to reveal the anomalies information, but searching the best projection directions is a computational intensive task. To improve the process efficiency, a parallel process algorithm under cluster system was presented. The combination of skewness and kurtosis was selected as projection index (PI). Using all the pixels- spectral as a special projection dierection set and searching the best projection directions in it. While parallel computing the PI value for each candidate dierection, the hyperspectral data was distributed to each computing node after partitioned evenly. After projecting each data subblock to a candidate direction in parallel, the index computation was transformed and decomposed. This makes all the data needed during index computation be in local memory for each node and decreases the communication. Furthermore, a "be host in turn" method was put forward to improve the degree of load balance. Using an operative modular imaging spectrometer data to test the efficiency on cluster, the results show that the parallel algorithm achieves good parallel performance.
Keywords�� remote sensing   image anomalies detection   parallel algorithm   projection pursuit   special projection direction set     
Received 2008-03-17;
About author: �� ά(1984-),��,���ϳ�����,˶ʿ��,wangweibh@126.com.
���ñ���:   
�� ά, �Ի۽�, �� ��.����ͶӰѰ�ٵĸ߹���ͼ���쳣��Ⲣ���㷨[J]  �������պ����ѧѧ��, 2009,V35(3): 342-346
Wang Wei, Zhao Huijie, Dong Chao.Parallel algorithm of anomalies detection in hyperspectral image with projection pursuit[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2009,V35(3): 342-346
���ӱ���:  
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2009/V35/I3/342
Copyright 2010 by �������պ����ѧѧ��