基于Daubechies小波的图像边缘检测技术  

Image edge detection technology based on Daubechies wavelet

作　　者：毛安定[1] 管一弘[1] 段锐[1] 王艳华[1] 吕梁[2] 季云海[2] 

机构地区：[1]昆明理工大学理学院,云南昆明650093 [2]云南省昆明市第一人民医院,云南昆明650093

出　　处：《图学学报》2012年第1期63-67,共5页Journal of Graphics

基　　金：云南省自然科学基金资助项目(2005F0194m)

摘　　要：利用Daubechies正交小波变换的性质,通过Mallat多尺度分析方法对图像进行小波变换,把图像分解成低频轮廓,水平高频、垂直高频和斜线高频四个部分。针对图像边缘主要集中在高频部分,该文先保持小波变换后的高频小波系数,同时对低频小波系数进行再次小波变换,提取出次高频信号的边缘信息。最后对保留下来的高频小波系数和次高频小波系数进行逆变换获取最大边缘信息。In this paper, an image wavelet transform is conducted by using the features of Daubechies orthogonal wavelet and the Mallat multi-scale analysis method. The image is decomposed into four parts of a low-frequency contour, the horizontal high-frequency, the vertical high-frequency and the slash high frequency. Because the image edge mainly concentrates in the high-frequency parts, the high-frequency wavelet coefficients are reserved while low-frequency wavelet coefficients are conducted of wavelet transform again, extracting the second high-frequency signals from low-frequency contour parts. Finally, the maximization of edge information of image is achieved in extraction by use of inverse transformation of the high-frequency wavelet coefficients and the second high-freouencv wavelet coefficients_

关 键 词：DAUBECHIES小波 小波变换 多尺度分析 边缘检测 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]