基于小波和快速模糊算法的医学图像边缘检测

在医学图像中,常常需要得到图像的边缘轮廓线,以便诊断病变情况.为适应这种需求,文中提出了基于小波分解和快速模糊算法的医学图像边缘检测方法.针对用模糊算法构造相应隶属函数进行图像边缘检测中存在的低频信号得不到有效利用、边缘检测速度较慢等问题,利用小波分解和快速模糊算法的优点构造边缘检测算法.这种方法使得小波分解后的低频信号中所包含的有用信息得到了利用,简化了算法并提高了算法的效率,增强了算法的适应性.文中算法检测出的图像边缘与经典边缘算子提取的图像边缘相比较,结果更加清晰完整.

Edge Detection of Medical Image Based on Little Wave and Fast Fuzzy Algorithm

People often need to get the edge line of the picture in the medical pictures, in order to diagnose the pathological change situation. So the edge detection method of medical picture based on the small wave and the fast fuzzy algorithm is proposed in the article in order to meet this demand. The advantage of little wave and fast fuzzy algorithm is used to construct edge measure algorithms in order to solve some problems such as the low frequency signal can not be utilized effectively, the speed measured on the edge is relatively low and so on when you measure the edge of picture using the jurisdiction of function and correspondingly with the structure of the fuzzy algorithm. Fast fuzzy algorithm on edge measure adopts the simple one which is under the jurisdiction of one degree of function. It can transform the picture into matrix which is under the jurisdiction of degrees quickly and transform against matrix which is under the jurisdiction of degrees into picture quickly. The useful information included in the low frequency signal after making the small wave decomposition is utilized. So it has simplified the algorithms and improved the efficiency of the algorithm, and has strengthened the adaptability of the algorithm. Compared with the picture edge classical edge operator, the new one is clearer and more intact.