计算机应用 ›› 2012, Vol. 32 ›› Issue (05): 1296-1299.

• 图形图像处理 • 上一篇    下一篇

基于多尺度主成分分析的图像局部方向估计算法

廖宇   

  1. 湖北民族学院 信息工程学院,湖北 恩施 445000
  • 收稿日期:2011-11-03 修回日期:2011-12-16 发布日期:2012-05-01 出版日期:2012-05-01
  • 通讯作者: 廖宇
  • 作者简介:廖宇(1979-),男,湖北建始人,讲师,硕士,主要研究方向:信号与信息处理。
  • 基金资助:

    湖北省教育厅科学研究项目(Q20111907,D20101903)

New local orientation estimation method of images based on principal component analysis

LIAO Yu   

  1. School of Information Engineering, Hubei University for Nationalities, Enshi Hubei 445000, China
  • Received:2011-11-03 Revised:2011-12-16 Online:2012-05-01 Published:2012-05-01
  • Contact: LIAO Yu

摘要: 现有的大多数图像方向估计算法都对噪声非常敏感。因此,提出了一种基于主成分分析(PCA)和多尺度梯度金字塔分解的图像局部方向估计算法,其中主成分分析用于找到局部方向的最大似然(ML)估计。所提出的算法对于噪声图像非常鲁棒。在实验中,通过对模拟图像的和真实图像的方向估计,该算法都可以得到较好的估计效果,对噪声的鲁棒性较强,并且计算速度非常快。

关键词: 主成分分析, 多尺度分解, 局部方向估计, 边缘提取

Abstract: Most of the existing image orientation estimation algorithms are very sensitive to noise. Therefore, this paper presented a new local orientation estimation method of image, which was based on Principal Component Analysis (PCA) and multi-scale gradient pyramid decomposition. The PCA was applied to search for the Maximum Likelihood (ML) estimation of the local orientation of block in image. Through presenting the local orientation estimation both of simulated images and real images, the experimental results show that the proposed algorithm has excellent robustness against noise, its speed is very fast and the accuracy is very high.

Key words: Principal Component Analysis (PCA), multi-scale decomposition, local orientation estimation, edge extraction

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