ISSN 1000-1239 CN 11-1777/TP

• 论文 • 上一篇    

一种新的脊波变换方法

赵小明1,2 叶喜剑1   

  1. 1(台州学院计算机系 台州 317000) 2(浙江工业大学信息工程学院 杭州 310014) (tzxyzxm@yahoo.com.cn)
  • 出版日期: 2008-05-15

A New Approach to Ridgelet Transform

Zhao Xiaoming1,2 and Ye Xijian1   

  1. 1(Department of Computer Science, Taizhou University, Taizhou 317000) 2(College of Information Engineering, Zhejiang University of Technology, Hangzhou 310014)
  • Online: 2008-05-15

摘要: 小波变换适用于表示具有各向同性奇异性对象的局部特性,脊波变换适用于表示具有各向异性奇异性对象的局部特性,但是各自对于对方所适用的局部特性的应用效果却不明显.提出了一种新的对脊波理论加以改进的多分辨分析方法——拟脊波多分辨分析方法.该方法统一了小波理论和脊波理论,使小波理论和脊波理论成为该方法的两种特殊情形.同时它具有对各向同性和异性的奇异性对象的辨识能力.通过实验比较表明,该方法对小波理论和脊波理论优点的组合、缺点的规避相当明显,在图像去噪应用中具有更强的灵活性.

关键词: 小波变换, 脊波变换, Radon变换, 拟Radon变换, 拟脊波变换

Abstract: Wavelet transform is suitable for expressing local characteristics of the object which has isotropic singularity. but to the anisotropic singularity, wavelet is not the best tool because it will cause the blur of image edges and details. Ridgelet transform actually is a wavelet basis function with a added parameter which is characterized direction. It has the same ability in local timefrequency resolution as wavelet transform. Meanwhile, ridgelet transform has a strong ability to identify and choose the direction. So it is an effective method to express the local characteristics of the object which has anisotropic singularity. But each of them is applied ineffectively to the local characteristics suitable for the other. Presented in this paper is an improved multiresolution method based on ridgelet theory, that is, quasiridgelet multiresolution analysis method. This method unifies wavelet theory and ridgelet theory, and makes wavelet theory and ridgelet theory to be its two special cases. Meanwhile, it has the discernment of isotropic and isometric singularity object. Thus the transformation method is able to maintain the ridgelet theory possessing superiority on the line characteristic detection, and enhances the point characteristic detection at the same time. By experimental comparison, it is shown that the effects of this method on combining the advantages and evading the disadvantages of wavelet theory and ridgelet theory are quite obvious, having more flexibility in the application of eliminating image noise.

Key words: wavelet transform, ridgelet transform, Radon transform, quasi Radon transform, quasi ridgelet transform