图像分割的二维最大熵遗传算法

2 - D Maximum Entropy Method of Image Segmentation Based on Genetic Algorithm

将遗传算法运用于二维最大熵图像阈值分割法 .首先对二维阈值坐标进行编码 ,然后依据二维最大熵准则建立适应度函数 ,在适当的交叉率和变异率下 ,最终实现强噪声干扰下图像的有效分割 .分割实验表明 ,文中方法较一维最大熵法具有更强的抗噪声能力 。

D thresholds are coded, then the fitness function is established according to the criterion function of 2 D maximum entropy. Finally the image which is disturbed by serious noise is segmented effectively under the proper crossover rate and mutation rate. Segmentation examples show that the method proposed has greater resistance capability to noise than 1 D maximum entropy approach, and is faster than the common 2 D maximum entropy approach.