摘要： 传统特征匹配的相似性度量方法多假定特征为直方图形式,结构单一。结构相似性(SSIM)度量在图像质量评价领域表现良好,但其鲁棒性较差。针对上述问题,提出一种扩展结构相似性度量方法。从空间网格提取特征阵列的三阶张量结构丰富特征信息,以加和形式修改SSIM度量,并引入权值,将张量特征结构用于相似性度量,建立高鲁棒性的相似性度量方法。提供点积形式的显性特征映射,以加快相似性度量速度。对关键点匹配和图像检测任务进行实验,结果表明,与传统相似性度量方法相比,该方法具有鲁棒性更强的匹配效果,并且计算效率有较大提高。
关键词:
结构相似性,
特征匹配,
特征映射,
张量结构,
鲁棒性
Abstract: The similarity measure method of traditional feature matching is mostly assumed to be a histogram with a single structure.Structural Similarity(SSIM) measures perform well in the field of image quality evaluation,but their robustness is poor.Aiming at this problem,a method to measure the structural similarity is proposed.The third-order tensor structure of feature array is extracted from the spatial grid,the feature information is enriched,the SSIM metric is modified by summation,weights are introduced,and the tensor feature structure is used for the similarity measure to establish high robust similarity measurement method.The dot product form of explicit feature maping is provided to speed up the similarity measure.Experimental results for key-point matching and image retrieval show that,compared with the traditional methods,the proposed method has better matching effect with more robustness and faster computation speed.
Key words:
Structural Similarity(SSIM),
feature matching,
feature mapping,
tensor structure,
robustness
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