matlab 图像二维直方图

clc;
clear all;
close all;
tic
I=imread('corner.png');
% I=double(I);
 f=rgb2gray(I);
 figure,imshow(f),title('原图像');
  figure,imhist(f),title('一维直方图');
[m,n,d]=size(f)
A=f;
for i=1:1:256
    for j=1:1:256
        twodim2(i,j)=0;
    end
end
 J = imnoise(f,'gaussian',0.05);
 figure,imshow(J),title('加躁后的图像');
 figure,imhist(J),title('一维直方图');
H=fspecial('average');
 k=imfilter(J,H);
% k=medfilt2(A)
for j=1:1:n;
    for i=1:1:m;
        m1=J(i,j);
        m2=k(i,j);
        twodim2(m1+1,m2+1)= twodim2(m1+1,m2+1)+1;
        
    end
end
i=1:1:256;
j=1:1:256;
figure;
 mesh(i,j,twodim2(i,j)/(m*n));

title('二维直方图')
toc


rusult:

二维直方图：

eg2:

% 二维直方图，x轴是像素灰度值，y轴是邻域平均处理后的灰度值，z轴是统计的像素数目
 clear
 clc
 % 读取图像并作邻域平均处理
 I = im2uint8(imread('rice.png'));
 f = im2double(I);
 w = fspecial('average',3);
 I_avr = im2uint8(imfilter(f,w));
 % 统计图中存在的灰度值
 h_gray = imhist(I);
 h_avr = imhist(I_avr);
 ind_gray = find(h_gray>0)-1;
 ind_avr = find(h_avr>0)-1;
 % 预分配2D直方图数据矩阵
 [X,Y] = meshgrid(ind_gray,ind_avr);
 [m,n] = size(X);    % m是grayind_avr的长度，n是grayind的长度
 data = zeros(m,n);
 % 遍历存在的灰度与均值，寻找对应像素并计数
 for i=1:m
     for j=1:n
         gray = (X(i,j)==I);
         avr = (Y(i,j)==I_avr);
         data(i,j) = length(find(gray & avr));
     end
 end
 % 绘图
 surf(X,Y,data)
 xlabel('灰度值')
 ylabel('邻域均值')
 zlabel('像素数')
 view(90,90)

result: