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基于非下采样轮廓波的图像检索
引用本文:陈丽燕,陈建华.基于非下采样轮廓波的图像检索[J].福州大学学报(自然科学版),2012,40(2):172-175,216.
作者姓名:陈丽燕  陈建华
作者单位:福州大学数学与计算机科学学院
基金项目:国家星火计划资助项目(2007EA720021)
摘    要:提出一种基于非下采样轮廓波的图像检索方法.首先对图像进行预处理;然后利用非下采样轮廓波的平移不变特性,将像素点分为强边缘、弱边缘和噪声点三类;最后忽略噪声点,提取强边缘和弱边缘的各个子带的均值和方差等作为特征进行检索.实验结果显示,与轮廓波等方法相比,该方法具有更高的鲁棒性、检索效率更高且特征维数低.

关 键 词:图像检索  非下采样  轮廓波  边缘  噪声

Image retrieval based on nonsubsampled contourlet
CHEN Li-yan,CHEN Jian-hua.Image retrieval based on nonsubsampled contourlet[J].Journal of Fuzhou University(Natural Science Edition),2012,40(2):172-175,216.
Authors:CHEN Li-yan  CHEN Jian-hua
Institution:(College of Mathematics and Computer Science,Fuzhou University,Fuzhou,Fujian 350108,China)
Abstract:This paper proposes a strategy for image retrieval based on nonsubsampled contourlet.Firstly,preprocessing the image,then,the pixels are divided into strong edges,weak edges and noises.Finally,the means and variables of nonsubsampled contourlet transform coefficients matrix in different subbands and various directions of strong edges and weak edges were extracted to form the feature vectors for image retrieval.Compared to the contourlet transform,this approach can not only get higher accuracy,but also reduce the dimension of feature vectors,and is more robust.
Keywords:image retrieval  nonsubsampled  contourlet  edges  noises
本文献已被 CNKI 等数据库收录!
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