| 基于分块互信息和量子粒子群算法的图像配准 |
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| 引用本文： | 陈庆芳,吴小俊.基于分块互信息和量子粒子群算法的图像配准[J].数据采集与处理,2011,26(4):473-477. |
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| 作者姓名： | 陈庆芳 吴小俊 |
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| 作者单位： | 江南大学信息工程学院,无锡,214122 |
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| 基金项目： | 教育部新世纪优秀人才计划(NCET-06-0487)资助项目; 国家自然科学基金(60572034,60973094)资助项目; 江苏省自然科学基金(BK2006081)资助项目; 江南大学创新团队研究计划(JNIRT0702)资助项目 |
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| 摘 要： | 多模图像的配准是图像融合等图像处理需要先行解决的问题.本文提出了一种基于分块互信息和量子粒子群的配准方法,在配准中利用分块互信息值为相似性测度,并用量子粒子群算法求解配准所需的空间变换参数.实验表明:该方法能够避免陷入局部极小值而且速度得到明显改善,其运用于多模图像配准,可以得到理想的效果.
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| 关 键 词： | 多模图像 分块互信息 量子粒子群优化 图像配准 |
Image Registration Based on Block Mutunal Information and Quantum-Behaved Particle Swarm Optimization |
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| Chen Qingfang,Wu Xiaojun.Image Registration Based on Block Mutunal Information and Quantum-Behaved Particle Swarm Optimization[J].Journal of Data Acquisition & Processing,2011,26(4):473-477. |
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| Authors: | Chen Qingfang Wu Xiaojun |
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| Affiliation: | Chen Qingfang,Wu Xiaojun(School of Information Engineering,Jiangnan University,Wuxi,214122,China) |
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| Abstract: | Multimodality image registration is important in military application.It is the first step for image fusion and other image processing. A new image registration method based on block mutual information and quantum-behaved particle swarm optimization algorithm is proposed.In the process of registration,the block mutual information is used for the similar measure,and the transformation parameters are calcultaed by using the quantum-behaved particle swarm optimization algorithm.Experimental results show that t... |
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| Keywords: | multi-modality image block mutual information quantum-behaved particle swarm optimization(QPSO) image registration |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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