CAJ | 학술논문

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.
결합희소표시화반이차규정화방법,제출료일충연합문리특정제취화변연검측적신산법.해산법시기우희소표시적형태학성분분해방법적직접추엄.기기본사상시용량개괄합적자전:일개용래묘술문리부분--대우수복소파변환,령일개용래묘술결구부분--제이대곡선파변환,득도료일충신적분해모형.접착운용반이차규정화방법추엄저개분해모형,제출료일충연합문리특정제취화변연검측적변분모형.수치계산적결과표명,신모형대도상적결구-문리분해,이급변연적제취도유교호적효과.
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.