【摘要】 由于医学图像会同时含有物体边缘、物体阴影与噪声,针对于医学图像边缘检测中很难从噪音或者微小几何特征中区分出精确边缘的问题,本文提出了一种基于超熵的检测嘈杂医学图像边缘的算法,引入超熵系数,通过适当确定超熵的参数值,不仅可以抑制噪声,还可以适应图像的不同边缘检测。通过试验,发现所提出的算法相对于其他方法性能具有明显的提高,运行时间缩短至80%。更多还原

【Abstract】 Because medical images will also contain the edges of objects, object shadows and noise, for it is difficult to distinguish from noise or small geometric features a precise edge issues in medical image edge detection, we propose a super-entropy detection of noisy medical image edge algorithm, the introduction of super-entropy factor determined by the appropriate parameter values over entropy can not only suppress noise, it can also adapt to different image edge detection. By algorithm tests and found that the proposed method compared to other has significantly improved performance and run time is reduced to 80%.更多还原