自适应尺度参数的非均匀图像快速水平集分割

NON-UNIFORM IMAGE FAST LEVEL SET SEGMENTATION BASED ON ADAPTIVE SCALE PARAMETERS

由于不同对象区域之间强度范围的重合,在存在强度不均匀的情况下很难分割图像。针对这一问题,提出一种新的水平集分割方法。在非均匀图像模型的基础上,推导出图像域的最优分割平面。在平面上,提出一种新的基于区域的压力函数,并在水平集公式中定义一个能量泛函。通过对能量泛函最小化,在对非均匀图像分割的同时,对偏置场进行估计。另外,为了准确估计偏置场,针对核函数设计一种新的自适应尺度参数。在真实图像和人工合成图像上的实验结果表明,该方法在精度、效率和鲁棒性方面有很好的优越性。

Because of the overlap of intensity range between different object regions,it is difficult to segment the image when the intensity is not uniform.To solve this problem,a new level set segmentation method is proposed.Based on the non-uniform image model,the optimal segmentation plane of image domain was derived.On the plane,a new region-based pressure function was proposed,and an energy functional was defined in the level set formula.By minimizing the energy functional,the bias field was estimated while the non-uniform image was segmented.In addition,in order to estimate bias field accurately,a new adaptive scale paremeter was designed for kernel function.The experimental results on composite images and real images show the superiority of this method in accuracy,efficiency and robustness.