基于贝叶斯算法的图像像素分割

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%20170925 chenkexin
%基于灰度特征的贝叶斯分割
clear;clc;
%%%%%%%%%%%%%%%%%数据准备%%%%%%%%%%%%%%%%%%%%%%%%%%%
load（‘array_sample.mat‘）;
load（‘Mask.mat‘）;
img_with_fish = imread（‘.\309.bmp‘）;
%构造3通道掩膜
mask3d（::1） = Mask;
mask3d（::2） = Mask;
mask3d（::3） = Mask;
%转换图像为双精度
img_with_fish = im2double（img_with_fish）;
%得到鱼图像
fish = img_with_fish.*mask3d;
grey_fish = rgb2gray（fish）;
%%%%%%%%%%%%%%%%%%%%类条件参数估计%%%%%%%%%%%%%%%%%%%%
%初始化两类样本个数
pos = 0;neg = 0;
%初始化两类样本灰度值之和
possum = 0;negsum = 0;

%计算两类样本个数与特征值之和
for i = 1:7696
    if array_sample（i5） == 1
        pos = pos + 1;
        possum = possum + array_sample（i1）;
    else
        neg = neg + 1;
        negsum = negsum + array_sample（i1）;
    end
end
%假定为正太分布，得到极大似然估计均值
u_pos = possum/pos;
u_neg = negsum/neg;

%同理得到极大似然估计两类分布函数标准差
sigma_pos = 0;sigma_neg = 0;
for i = 1:7696
    if array_sample（i5） == 1
        sigma_pos = sigma_pos + （array_sample（i1） -