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采用局域像素匹配的随机抽样一致改进算法
引用本文:戴卫华,刘盛春,赵慎,彭华,张昊,黄志刚,李小林. 采用局域像素匹配的随机抽样一致改进算法[J]. 国防科技大学学报, 2021, 43(4): 38-43
作者姓名:戴卫华  刘盛春  赵慎  彭华  张昊  黄志刚  李小林
作者单位:信息工程大学信息系统工程学院,河南郑州 450001;哈尔滨工程大学水声工程学院,黑龙江哈尔滨 150006;陆军工程大学石家庄校区,河北石家庄 050003;盲信号处理国防科技重点实验室,四川成都 610041;拉盖尔电子科技有限公司,湖南长沙 410073
基金项目:国家自然科学基金资助项目(61802430)
摘    要:为提高图像拼接的配准精度和稳健性,提出基于局域像素匹配的随机抽样一致改进算法.在完成尺度不变特征变换算子或其他算子图像特征提取、特征匹配之后,利用独立于特征匹配点的局域像素,通过参考图像局域像素与映射的待拼接图像局域像素匹配,优选4对最佳特征匹配点,确定最佳单应矩阵.实验结果表明:与随机抽样一致经典算法相比,该方法未明...

关 键 词:图像拼接  单应矩阵  随机抽样一致算法  像素匹配
收稿时间:2019-11-20

Improved random sampling consensus algorithm using local pixel matching
DAI Weihu,LIU Shengchun,ZHAO Shen,PENG Hu,ZHANG Hao,HUANG Zhigang,LI Xiaolin. Improved random sampling consensus algorithm using local pixel matching[J]. Journal of National University of Defense Technology, 2021, 43(4): 38-43
Authors:DAI Weihu  LIU Shengchun  ZHAO Shen  PENG Hu  ZHANG Hao  HUANG Zhigang  LI Xiaolin
Affiliation:College of Information Systems Engineering, Information Engineering University, Zhengzhou 450001, China;College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150006, China;Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, China;National Key Laboratory on Blind Signal Processing, Chengdu 610041, China; Laguerre Electronic Technology Company, Changsha 410073, China
Abstract:In order to improve the registration precision and robustness of image splicing, an improved random sampling consensus algorithm based on local pixel matching was proposed. After completing image feature extracting and feature matching with the scale invariant feature transform operator or other operator, using the local pixels that are independent of feature matching points, then the optimal configuration of the four pairs of feature matching points, and the best homography matrix were determined by matching the local pixel of the reference image with the mapped local pixel of the image to be stitched. The experimental results show that, compared with the classical random sampling consensus algorithm, the computation time is close, the homography matrix is more accurate, and the image mosaic is more robust.
Keywords:image splicing   homography matrix   random sampling consensus algorithm   pixel matching
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