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作 者:鲍文霞[1,2] 余国芬 胡根生[1] 阎少梅[1] BAO Wen-xia;YU Guo-fen;HU Gen-sheng;YAN Shao-mei(School of Electronics and Information Engineering,Anhui University,Hefei 230601;Anhui Province Key Laboratory of Polarization Imaging Detection Technology,Hefei 230031,China)
机构地区:[1]安徽大学电子信息工程学院,安徽合肥230601 [2]偏振光成像探测技术安徽省重点实验室,安徽合肥230031
出 处:《计算机工程与科学》2018年第3期494-499,共6页Computer Engineering & Science
基 金:国家自然科学基金(61401001;61501003);安徽省自然科学基金(1408085MF121);偏振光成像探测技术安徽省重点实验室开放基金
摘 要:为了提高基于谱特征的图像匹配算法的精度和鲁棒性,提出了一种基于最大池的谱特征匹配算法。首先,利用图像特征点邻域信息提取具有旋转不变性和亮度线性变化不变性的谱特征;其次,将以谱特征描述的特征点作为节点、特征点之间的欧氏距离作为边构造属性关系图,将图像匹配问题转化为图匹配问题;最后,引入最大池匹配策略获取图匹配结果。大量实验结果表明,该算法提高了谱特征匹配算法的精度和鲁棒性。In order to improve the accuracy and robustness of image matching algorithms based on spectral feature,a spectral feature matching algorithm based on maximum pool is proposed.Firstly,we use the neighborhood information of image feature points to extract spectral features that are invariant to rotation and the linearity of brightness changes.Secondly,we use the feature points described by spec-tral features as nodes and the Euclidean distance between feature points as edge properties,and trans-form the image matching problem into graph matching problem.Finally,the maximum pool matching strategy is introduced to obtain the graph matching results.A large number of experimental results show that the proposed algorithm improves the accuracy and robustness of the spectral feature matching algorithm.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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