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基于简单Schur凹函数的图像配准测度研究 被引量:1

Novel Measures Based on Simple Schur Concave Function for Image Registration
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摘要 使用互信息或归一化互信息进行图像配准时,由于噪声、模态、插值等影响,测度函数存在许多局部极值,收敛范围较窄,有可能导致误配准.该文根据一个简单的Schur凹函数,充分利用它的特殊上凸性来消除噪声等引起的小概率分布,并由Jensen-Schur测度、广义距离测度和f信息测度的定义,构造了六种新测度.从运算时间、收敛性能、抗噪鲁棒性方面,对这六种测度、互信息和归一化互信息进行了比较和分析.实验结果表明,Jensen-Schur-beta和D-beta测度的收敛性能优于其它测度,抗噪声能力强于其它测度,运算速度快于互信息和归一化互信息. When the influence of noise,interpolation and image modality is considered, the image registration method based on mutual information or normalized mutual information may cause local extrema, small convergence area, and even inaccurate registration. According to a simple Schur concave function and the definition of Jensen-Schur measure, generalized divergence measure and f information measure, six new measures were constructed. The Schur function with special concave characteristics can filter the small probability distribution caused by noise, interpolation and so on. The characters of six new measures, mutual information and norrnalized mutual information are analyzed and compared by applying them to rigid registration. The results of tests show that Jensen-Schur-beta and D-beta measures outperform other measures in convergence performance and noise ilmnunity, and they are time saving in comparison with mutual information and normalized mutual information measures.
出处 《电子学报》 EI CAS CSCD 北大核心 2008年第12期2328-2332,共5页 Acta Electronica Sinica
基金 国家"863"计划资助项目(No.2006AA02Z4D9) 山东省自然科学基金资助项目(No.Z2006C05)
关键词 图像配准 Schur凹函数 Jensen-Schur测度 互信息 image registration Schur concave function Jensen-Schur measure mutual information
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参考文献9

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同被引文献13

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