一种基于图像灰度和方差信息的图像分割方法

An image segmenting method based on image gray and variance information

针对C-V方法对非二值图像分割不理想,运行效率不高的问题,提出一种改进的C-V方法。在C-V方法只运用图像灰度信息的基础上,加入基于图像局部方差的信息,并且设置加权参数k,通过k来控制基于图像的灰度信息和方差信息的驱动力在整个图像分割驱动力中的比重,使得改进C-V方法能利用图像区域灰度信息和区域方差信息对非二值图像进行分割,同时应用隐式方案的数值实现方式对改进方法进行数值实现。图像分割实验结果表明,该方法能够更为准确地提取非二值图像边界,减少迭代次数。

An improved C-V method was proposed aiming at unfavorable result and low efficiency when the original C-V method was used to segment non-binary image. Considering that the original C-V method only used the gray information, the improved C-V method added local variance information of the image. In addition, the improved C-V method set a weight parameter k, and by adjusting k it can control the proportions of the driving force based on the gray and variance information in the process of segmenting the entire image. Thus, this method can segment non-binary image by the regional gray and variance information. Simultaneously, the implicit scheme was used in the process of the numerical realization of the improved method. The experimental results show that the improved C-V method can extract edge of non-binary image more accurately and reduce the times of iteration.