| 多幅图像的自动拼接算法研究 |
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| 引用本文： | 赵毅力.多幅图像的自动拼接算法研究[J].计算机工程与应用,2012,48(34):152-157. |
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| 作者姓名： | 赵毅力 |
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| 作者单位： | 西南林业大学计算机与信息学院,昆明,650224 |
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| 基金项目： | 云南省应用基础研究项目 |
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| 摘 要： | 提出一种基于特征点的多幅图像自动拼接算法。根据SIFT或SURF算法在图像的尺度空间中提取特征点,对特征点进行亚像素定位,并赋予主方向。根据特征点邻域信息分布计算得到特征向量后,基于k-d树进行最近邻和次最近邻搜索,利用最近邻特征点距离与次近邻特征点距离之比得到初始匹配点对。使用RANSAC(Random Sample Consensus)算法剔除错误匹配特征点对,同时对图像之间的变换参数进行鲁棒估计,使用多频带融合算法消除拼接痕迹。实验验证了该算法能够完成多幅图像的自动无缝拼接。
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| 关 键 词： | 图像拼接 特征匹配 鲁棒估计 图像融合 |
Automatic multiple images stitching algorithm research |
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| ZHAO Yili.Automatic multiple images stitching algorithm research[J].Computer Engineering and Applications,2012,48(34):152-157. |
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| Authors: | ZHAO Yili |
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| Affiliation: | ZHAO Yili College of Computer and Information,Southwest Forestry University,Kunming 650224,China |
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| Abstract: | This paper presents an automatic multiple images stitching algorithm based on feature points. The algorithm first extracts the SIFT or SURF feature points from the scale space of the image, then locates feature points on the sub-pixel coordinates, and gives the main orientation. Initial feature points matching can be calculated by using the k-nearest neighbor search based on k-d tree, and distance ratio of the nearest neighbor feature point and the next nearest neighbor feature point. Then using RANSAC （Random Sample Consensus） algorithm to match the initial feature points set, while transformation parameters between the two images can be estimated robustly. Seamless multi-image automatic stitching can be obtained by using multi-band blending algorithm. |
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| Keywords: | image stitching feature matching robust estimation image blending |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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