[an error occurred while processing this directive]
   
 
���¿��ټ��� �߼�����
   ��ҳ  �ڿ�����  ��ί��  Ͷ��ָ��  �ڿ�����  ��������  �� �� ��  ��ϵ����
�������պ����ѧѧ�� 2010, Vol. 36 Issue (6) :719-722    DOI:
���� ����Ŀ¼ | ����Ŀ¼ | ������� | �߼����� << | >>
���ڿ����˻�MRF�ĸĽ�SARͼ��ָ��
*
���������պ����ѧ ������Ϣ����ѧԺ, ���� 100191��
Modified SAR image segmentation method based MRF with fast simulated annealing

ժҪ
�����
�������
Download: PDF (884KB)   HTML 1KB   Export: BibTeX or EndNote (RIS)      Supporting Info
ժҪ 

����Markov�������MRF��Markov Random Field����SARͼ��ָ��������SARͼ��ĻҶȺͽṹ��Ϣ�����ڷָ��������Ч���ưߵ���������ýϸߵķָ��.�����෽����ȱ����ģ���˻�ļ������ܴ�.��Ը����⣬�����һ�ֻ��ڿ����˻�MRF�� SARͼ��ָ����.�÷�������SARͼ��Gibbs�ֲ������ԣ�����ȡȫ�����Ž�ʱ������Ѱ������ϵͳ��ռ��֧���λ��ij�ֱ�ǣ�������ռ֧���λ�ı�ǣ��ô˱�Ǹ���״̬����֮�������ô�ͳģ���˻�ķ����������״̬.���ڸ÷����������Gibbs�ֲ��������о�����ϵͳ״̬���£�����ܹ��������ȫ�����Ž�.������ʵSARͼ����д�����������֤���㷨����Ч��.

Service
�ѱ����Ƽ�������
�����ҵ����
�������ù�����
Email Alert
RSS
�����������
����
������
��Ľ��
�ؼ����� �ϳɿ׾��״�   ͼ��ָ�   ģ���˻�   �㷨     
Abstract��

Markov random field (MRF) approaches are able to implement better SAR image segmentation by combing the image intensity and structure information. However, this kind of approaches often obtains a global solution at the cost of computational burden. A fast simulated annealing method was presented by combing the prior knowledge of SAR image distribution and applied to the SAR image segmentation based MRF. In the process of segmentation based MRF, the fast method first searched the neighborhood of each pixel to find out whether there was a predominant marker. If yes, the pixel would be marked with this predominant marker in the updated segmentation field; if not, the pixel would be marked randomly as the traditional simulated annealing algorithm does. Because a prior judgment based on Gibbs distribution was introduced, the proposed method is able to obtain a global best solution very quickly. In the end, experiments were carried out on real SAR images and the results validate the feasibility and efficiency of the proposed method.

Keywords�� synthetic aperture radar   image segmentation   simulated annealing   algorithms     
Received 2009-05-13;
About author: ���򻪣�1976-�����У�����μ���ˣ���ʿ����xianghua2000.liu@gmail.com.
���ñ���:   
����, ������, ��Ľ��.���ڿ����˻�MRF�ĸĽ�SARͼ��ָ��[J]  �������պ����ѧѧ��, 2010,V36(6): 719-722
Liu Xianghua, Zhou Yinqing, Sun Muhan.Modified SAR image segmentation method based MRF with fast simulated annealing[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2010,V36(6): 719-722
���ӱ���:  
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2010/V36/I6/719
Copyright 2010 by �������պ����ѧѧ��