Improved Quantum-Inspired Immune Clonal Clustering Algorithm Applied to SAR Image Segmentation

摘要：

The goal of segmentation is to partition an image into disjoint regions. In this paper, the segmentation problem based on partition clustering is viewed as a combinatorial optimization problem. The original image is partitioned into small blocks by watershed algorithm, and the quantuminspired immune clonal algorithm is used to search the optimal clustering centre, and make the sequence of maximum affinity function as clustering result, and finally obtain the segmentation result. Experimental results show that the proposed method is effective for SAR image segmentation. SAR.

关键词： Segmentation problem partition clustering quantum-inspired immune clonal algorithm

作者: Y.Y. Li N.N. Wu R.C. Liu

作者单位: Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University,Xian 710071, China

会议类型: 国际会议

会议名称: 2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

会议地点: 成都

会议语种:英文

页码: 1566-1569

在线出版日期: 2011-10-24（万方平台首次上网日期，不代表论文的发表时间）