联合纹理提取和边缘检测的新方法  

New model combining texture extraction with edge detection

作　　者：殷海青[1] 江玲玲[2] 刘红卫[1] 

机构地区：[1]西安电子科技大学理学院,陕西西安710071 [2]中国石油大学(华东)数学与计算科学学院,山东东营257061

出　　处：《系统工程与电子技术》2010年第4期846-850,共5页Systems Engineering and Electronics

基　　金：国家自然科学基金(60603098)资助课题

摘　　要：结合稀疏表示和半二次规整化方法,提出了一种联合纹理特征提取和边缘检测的新算法。该算法是基于稀疏表示的形态学成分分解方法的直接推广。其基本思想是用两个适合的字典:一个用来描述纹理部分——对偶树复小波变换,另一个用来描述结构部分——第二代曲线波变换,得到了一种新的分解模型。接着运用半二次规整化方法推广这个分解模型,提出了一种联合纹理特征提取和边缘检测的变分模型。数值计算的结果表明,新模型对图像的结构纹理分解,以及边缘的提取都有较好的效果。A novel algorithm for extracting texture and detecting edge is presented based on sparse representations and half-quadratic regularization,which is a direct extension of the recently developed sparse-representation-based image decomposition method called morphological component analysis（MCA）.The basic idea presented in this method is the use of two appropriate dictionaries,one for the representation of texture parts——the dual tree complex wavelet transform and the other for the cartoon parts——the second generation of curvelet transform.It results in a new decomposition model.Then by using the method of half-quadratic regularization,a new method combining texture extraction with edge detection is derived based on the new decomposition model.Finally,numerical experiments show that the new method can decompose a given image into a cartoon and an oscillatory component better while detecting contour well and truly.

关 键 词：图像分解 边缘检测 曲线波变换 小波变换 稀疏表示 半二次规整化 

分 类 号：TN911.73[电子电信—通信与信息系统]