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实时影像匹配
相关语句
  real time image matching
     A real time image matching based on wavelet transform are discussed in this paper.
     讨论了一种基于小波变换的实时影像匹配方法。
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  相似匹配句对
     G.
     实时的G.
短句来源
     The Model of Image Matching Algorithm
     影像匹配算法模型
短句来源
     A real time image matching based on wavelet transform are discussed in this paper.
     讨论了一种基于小波变换的实时影像匹配方法。
短句来源
     Image Matching Based on Gentic Algorithms
     基于遗传算法的影像匹配
短句来源
     Real-Time Normalized Cross Correlation Algorithm
     实时的归一化相关匹配算法
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A real time image matching based on wavelet transform are discussed in this paper. Lipschith regularity exponent is introduced as the constraints during multiresolution feature extraction in order to ensure the reliability. A hierarchical matchimg is realized using orthogonal wavelet decomposition and reconstruction. Sub pixel matching is carried out by superposing edge feature on image. The experimental results demonstrate that above method is significant.

讨论了一种基于小波变换的实时影像匹配方法。在多尺度特征提取的过程中,采用了局域正则性指数作为约束条件,保证了特征提取的可靠性;利用小波正交分解与重建实现了分层匹配;同时,采用特征与影像叠加进行了亚像素匹配。经过试验证明,上述方法是行之有效的。

Fast image matching is an important method for aircraft navigation and motion analysis. A fast image matching method is adopted based on scale-space representation of image and a new robust Hausdorff distance. Firstly, preprocess of the reference image and real-time image uses Gaussian Low-filter with different σ according to their space resolution. Therefore, a high repeatability of the corners is obtained and registration probability is improved. Then, corners are detected quickly based on image geometric...

Fast image matching is an important method for aircraft navigation and motion analysis. A fast image matching method is adopted based on scale-space representation of image and a new robust Hausdorff distance. Firstly, preprocess of the reference image and real-time image uses Gaussian Low-filter with different σ according to their space resolution. Therefore, a high repeatability of the corners is obtained and registration probability is improved. Then, corners are detected quickly based on image geometric structure analysis. Finally, a novel robust Hausdorff distance is used to match reference image and real-time image. The experiment result shows that the method the paper suggested is robust to noise, illumination and scale changes. It can be obtainable for high registration probability at the condition of existing bigger gray level difference between reference image and real-time image.

快速影像匹配是进行影像时间序列分析与飞行器导航的重要方法。本文对待匹配影像进行高斯低通滤波预处理时,运用影像的尺度空间表达思想对不同分辨率的基准影像和实时影像选择了相应的σ值进行卷积滤波处理,使基准影像和实时影像具有相近的分辨率,从而提高两影像所提取角点的重复率,使得影像的正确匹配概率得到提高。然后用基于影像几何结构分析的改进的快速角点探测算法进行了影像的角点提取;最后用本文提出的改进的鲁棒Hausdorff距离进行了基准影像和实时影像的匹配。实验证明,本文方法对影像噪声和灰度变化不敏感,具有抗影像尺度变化的能力。在基准影像和实时影像灰度差变化较大的情况下,  收稿日期:2004 07 16;修回日期:2004 11 15基金项目:航天预研基金资助项目(2003)作者简介:安 如(1963 ),女,江苏淮安人,副教授,博士生,目前主要研究方向为数字影像处理与匹配。依然能取得较高的正确匹配概率。由于采用基于影像信息量评价的搜索策略和快速角点提取算法,匹配速度也较快。

An algorithm of image transform based on lifting scheme wavelet is researched.The update function for the algorithm is educed.Comparing the algorithm with linear lifting wavelet indicates that has not only capability of calculating at same position but also makes image edge clear.This algorithm provides image matching with rich information.Multiwindows matching algorithm is made using low frequency and high frequency image components in image matching.Experiences prove the algorithm is able to improve reliability...

An algorithm of image transform based on lifting scheme wavelet is researched.The update function for the algorithm is educed.Comparing the algorithm with linear lifting wavelet indicates that has not only capability of calculating at same position but also makes image edge clear.This algorithm provides image matching with rich information.Multiwindows matching algorithm is made using low frequency and high frequency image components in image matching.Experiences prove the algorithm is able to improve reliability and efficiency.

从第二代小波即小波提升方法出发,研究了一种反对称小波的影像变换算法、导出了其更新函数,并与线性提升算法进行了比较,结果表明,该算法不仅具有在位计算的特性,而且能够更好地突出影像边缘特征,为影像匹配提供了丰富的信息。在实时影像匹配中,同时采用了低频信息和高频分量,构成了多窗口匹配算法,试验证明,该算法能够提高匹配的效率和可靠性。

 
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