%%%%%% 求对比度%%%%%%clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image'); fpath=fullfile(pathname,filename);A=imread(fpath);figure(1);imshow(A);title('原图像')img=rgb2gray(A);figure(2);imshow(img);title('灰度后的');img1=imnoise(img,'salt & pepper',0.05); %加入椒盐躁声figure(3);imshow(img1);title('椒盐后的图像');%%% K近邻域滤椒盐噪声%%% 3*3%%% 找出与f（i，j）相近的像素值这里利用做差排序找出AAAA1=img1;AAAA1=double(AAAA1);%%%得到椒盐噪声图像[m,n]=size(AAAA1);for i=2:m-1for j=2:n-1ASD1=[AAAA1(i-1,j-1) AAAA1(i-1,j) AAAA1(i-1,j+1) ...AAAA1(i,j-1) AAAA1(i,j) AAAA1(i,j+1) ...AAAA1(i+1,j-1) AAAA1(i+1,j) AAAA1(i+1,j+1)];aa=ASD1; %%随机设定的一个数组b=AAAA1(i,j); %%取参照值a=aa(:); %%将给定数组化为一维的ab=(a(:)-b)'; %%将数组a与b做差abc=abs(ab);abc=sort(abc); %%差值取绝对值并排序[as1 as11] =find(abs((a(:)-b))==abc(1,1));as=[as1 as11];if ~isempty(abc(abc(:)~=abc(1,1)))if ~isempty(abc)abc1=abc(abc(:)~=abc(1,1));[as2 as22]=find(abs((a(:)-b))==abc1(1,1));as=[as1 as11;as2 as22];endendif ~isempty(abc1(abc1(:)~=abc1(1,1)))if ~isempty(abc1)abc2=abc1(abc1(:)~=abc1(1,1));[as3 as33]=find(abs((a(:)-b))==abc2(1,1));as=[as1 as11;as2 as22;as3 as33];endendif ~isempty(abc2(abc2(:)~=abc2(1,1)))if ~isempty(abc2)abc3=abc2(abc2(:)~=abc2(1,1));[as4 as44]=find(abs((a(:)-b))==abc3(1,1));as=[as1 as11;as2 as22;as3 as33;as4 as44];endendif ~isempty(abc3(abc3(:)~=abc3(1,1)))if ~isempty(abc3)abc4=abc3(abc3(:)~=abc3(1,1));[as5 as55]=find(abs((a(:)-b))==abc4(1,1));as=[as1 as11;as2 as22;as3 as33;as4 as44;as5 as55];endendif ~isempty(abc4(abc4(:)~=abc4(1,1)))if ~isempty(abc4)abc5=abc4(abc4(:)~=abc4(1,1));[as6 as66]=find(abs((a(:)-b))==abc5(1,1));as=[as1 as11;as2 as22;as3 as33;as4 as44;as5 as55;as6 as66];endend%%%% as即是与b值相近的值的坐标包括和b相等的（这里是与b 值相差为六种值的情况不一定是六个值可能等于也可能大于%%%% 将以下坐标的值取第二个到第六个即是与b值相近的5个）result=zeros(1,(length(as)-1));for VB=2:6result(VB-1)=a(as(VB,1));end %%%求前五个的均值AVERAGE=sum(result(:))/5;AAAA1(i,j)=AVERAGE;endendfigure(9)imshow(uint8(AAAA1));title('K近邻域滤椒盐噪声后的图像');clear;clc;I_gray=...[1 5 255 225 100 200 255 200;...1 7 254 225 100 10 10 9; ...3 7 10 100 100 2 9 6;...3 6 10 10 9 2 8 2;...2 1 8 8 934 2;...1 0 7 8 8 32 1;...1 1 8 8 72 2 1;...2 3 9 8 7 2 2 0]; %%%%%A可以是矩阵也可以是图像[height,width]=size(I_gray); %测量图像尺寸参数p=zeros(1,256); %预创建存放灰度出现概率的向量for i=1:heightfor j=1:widthp(I_gray(i,j) + 1) = p(I_gray(i,j) + 1) + 1;endends=zeros(1,256);s(1)=p(1);for i=2:256s(i)=p(i) + s(i-1); %统计图像中<每个灰度级像素的累积个数，s(i):0,1,```,i-1endfor i=1:256s(i) = s(i)*256/(width*height); %求灰度映射函数if s(i) > 256s(i) = 256;endend%图像均衡化I_equal = I_gray;for i=1:heightfor j=1:widthI_equal(i,j) = s( I_gray(i,j) + 1);endend %显示均衡化后的图像Dui_Bi_Du2=Qiu_Dui_Bi_Du(I_equal) %%%%%均衡化后的矩阵Dui_Bi_Du1=Qiu_Dui_Bi_Du(I_gray)clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image'); fpath=fullfile(pathname,filename);A=imread(fpath);img=rgb2gray(A);figure(1)imshow(img);Jiao_Du=input('请输入旋转角度'); %%%此旋转为逆时针方向theta=Jiao_Du/180*pi;img=double(img);[m,n]=size(img);mm=zeros();nn=zeros();tic %%%计时开始%%%%--求变换后的坐标值---%%%for i=1:mfor j=1:nmm(i,j)=round(i*cos(theta)-j*sin(theta));nn(i,j)=round(i*sin(theta)+j*cos(theta));endend%%%----------------------%%%Cha_Zhi_1=floor(abs(max(mm(:))-min(mm(:)))); %%横坐标最大差值//注意as=max(mm(:)) as=max(mm)的区别Cha_Zhi_2=floor(abs(max(nn(:))-min(nn(:)))); %%纵坐标最大差值//此处用as=max(mm(:))%%%由于上面求出的mm和nn可能会有0，这在数组中是不允许的故要找出0，统一加一定数值，是其全部为正值mm_min=min(mm(:));nn_min=min(nn(:)); %%找出行列中最小的负值%%%下面实现对mm nn的值统一变为大于0的整数[a,b]=size(mm);[aa,bb]=size(nn);for i=1:afor j=1:bmm(i,j)=mm(i,j)+abs(mm_min)+1;endendfor i=1:aafor j=1:bbnn(i,j)=nn(i,j)+abs(nn_min)+1;endend%%%%%%%-------------------------------%%%new_img=zeros(Cha_Zhi_1,Cha_Zhi_2); %%旋转后的新图像的画布大小%%%% 直接放大%%%%for i=1:mfor j=1:nnew_img(mm(i,j),nn(i,j))=img(i,j);endend%%%% 开始邻近插值%%%%for i=2:Cha_Zhi_1-1for j=2:Cha_Zhi_2-1if new_img(i,j)==0new_img(i,j)=round((new_img(i-1,j)+new_img(i+1,j)+new_img(i,j-1)+new _img(i,j+1)))/4;endendendtoc%%%计时结束figure(2);imshow(uint8(new_img));%%%%%----不等宽度、高度放大----%%%%%clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image'); fpath=fullfile(pathname,filename);A=imread(fpath);img=rgb2gray(A);figure(1)imshow(img);title('原图像');%%%%----width,height为原图像宽度和高度-----%%%% [Width,Height]=size(img);%%%%-----输入放大倍数的相关参数-----%%%%%Width_BeiShu=input('请输入宽度上的放大倍数：');Height_BeiShu=input('请输入高度上的放大倍数：');%%%%-----新图像画布大小-----%%%%%new_Width=round(Width_BeiShu*Width);new_Height=round(Height_BeiShu*Height);%%%%-----申请新画布------%%%%new_img=zeros(new_Width,new_Height);%%%%-----开始放大--------%%%%%%% 双线性差值算法中的四个顶点%%%Q12=0;Q11=0;Q21=0;Q22=0;%%% 开始差值%%%%%% 差值过程中要注意放大倍数不是整数时对坐标的取整%%% for i=1:Width-1for j=1:Height-1Q12=img(i,j+1);Q11=img(i,j);Q22=img(i+1,j+1);Q21=img(i+1,j);fora=(round((i-1)*Width_BeiShu)+1):round((i)*Width_BeiShu)forb=(round((j-1)*Height_BeiShu)+1):round((j)*Height_BeiShu)%%%双线性差值中的三个特征像素点%%%new_img((round((i-1)*Width_BeiShu)+1),b)=(i*Width_BeiShu-a)/(round( i*Width_BeiShu)-i)*Q11+(a-i)/(round(i*Width_BeiShu)-i)*Q12;%%%F(R1)new_img(round(i*Width_BeiShu),b)=(round(i*Width_BeiShu)-a)/(round( i*Width_BeiShu)-i)*Q12+(a-i)/(round(i*Width_BeiShu)-i)*Q22;%%%F(R2)new_img(a,b)=(round(j*Height_BeiShu)-b)/(round(j*Height_BeiShu)-j)*n ew_img(i,b)+(b-j)/(round(j*Height_BeiShu)-j)*new_img(round(i*Width_ BeiShu),b); %%%F(P);endendendendfigure(2);imshow(uint8(new_img));title('放大后的图像');clear all;close all;clc;jiaodu=input('请输入角度:'); %要旋转的角度，旋转方向为顺时针img=imread('E:\国创相关\国创\bmp图片\8位图像\017.bmp'); %这里v为原图像的高度，u为原图像的宽度imshow(img); %这里y为变换后图像的高度，x 为变换后图像的宽度[h w]=size(img);theta=jiaodu/180*pi;rot=[cos(theta) -sin(theta) 0;sin(theta) cos(theta) 0;0 0 1];pix1=[1 1 1]*rot; %变换后图像左上点的坐标pix2=[1 w 1]*rot; %变换后图像右上点的坐标pix3=[h 1 1]*rot; %变换后图像左下点的坐标pix4=[h w 1]*rot; %变换后图像右下点的坐标height=round(max([abs(pix1(1)-pix4(1))+0.5abs(pix2(1)-pix3(1))+0.5])); %变换后图像的高度width=round(max([abs(pix1(2)-pix4(2))+0.5abs(pix2(2)-pix3(2))+0.5])); %变换后图像的宽度imgn=zeros(height,width);delta_y=abs(min([pix1(1) pix2(1) pix3(1) pix4(1)])); %取得y方向的负轴超出的偏移量delta_x=abs(min([pix1(2) pix2(2) pix3(2) pix4(2)])); %取得x方向的负轴超出的偏移量for i=1-delta_y:height-delta_yfor j=1-delta_x:width-delta_xpix=[i j 1]/rot; %用变换后图像的点的坐标去寻找原图像点的坐标，%否则有些变换后的图像的像素点无法完全填充float_Y=pix(1)-floor(pix(1));float_X=pix(2)-floor(pix(2));if pix(1)>=1 && pix(2)>=1 && pix(1) <= h && pix(2) <= wpix_up_left=[floor(pix(1)) floor(pix(2))]; %四个相邻的点pix_up_right=[floor(pix(1)) ceil(pix(2))];pix_down_left=[ceil(pix(1)) floor(pix(2))];pix_down_right=[ceil(pix(1)) ceil(pix(2))];value_up_left=(1-float_X)*(1-float_Y); %计算临近四个点的权重value_up_right=float_X*(1-float_Y);value_down_left=(1-float_X)*float_Y;value_down_right=float_X*float_Y;imgn(i+delta_y,j+delta_x)=value_up_left*img(pix_up_left(1),pix_up_left( 2))+ ...value_up_right*img(pix_up_right(1),pix_up_right(2))+ ...value_down_left*img(pix_down_left(1),pix_down_left(2))+ ...value_down_right*img(pix_down_right(1),pix_down_right(2));endendendfigure,imshow(uint8(imgn))clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image'); fpath=fullfile(pathname,filename);image1=imread(fpath);%%%参数调整Fa Fb Ga Gbimage=image1(:,:,1);figure(1);imshow(uint8(image));title('原图')[m,n]=size(image);newimage=zeros(m,n);km1=input('输入原图像灰度值一:');km2=input('输入原图像灰度值二:');kn1=input('展宽后的灰度值一:');kn2=input('展宽后的灰度值二:');for i=1:mfor j=1:nif image(i,j)<km1newimage(i,j)=kn1*image(i,j)/km1;elseif image(i,j)<km2newimage(i,j)=(kn2-kn1)/(km2-km1)*(image(i,j)-km1)+kn1;elsenewimage(i,j)=(255-kn2)/(255-km2)*(image(i,j)-km2)+kn2;endendendfigure(2);imshow(uint8(newimage));title('处理后的')clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image');fpath=fullfile(pathname,filename);A=imread(fpath);img=rgb2gray(A);figure(1)imshow(img);Jiao_Du=input('请输入旋转角度'); %%%此旋转为逆时针方向theta=Jiao_Du/180*pi;img=double(img);[m,n]=size(img);mm=zeros();nn=zeros();tic %%%计时开始%%%%--求变换后的坐标值---%%%for i=1:mfor j=1:nmm(i,j)=round(i*cos(theta)-j*sin(theta));nn(i,j)=round(i*sin(theta)+j*cos(theta));endend%%%----------------------%%%Cha_Zhi_1=floor(abs(max(mm(:))-min(mm(:)))); %%横坐标最大差值//注意as=max(mm(:)) as=max(mm)的区别Cha_Zhi_2=floor(abs(max(nn(:))-min(nn(:)))); %%纵坐标最大差值//此处用as=max(mm(:))%%%由于上面求出的mm和nn可能会有0，这在数组中是不允许的故要找出0，统一加一定数值，是其全部为正值mm_min=min(mm(:));nn_min=min(nn(:)); %%找出行列中最小的负值%%%下面实现对mm nn的值统一变为大于0的整数[a,b]=size(mm);[aa,bb]=size(nn);for i=1:afor j=1:bmm(i,j)=mm(i,j)+abs(mm_min)+1;endendfor i=1:aafor j=1:bbnn(i,j)=nn(i,j)+abs(nn_min)+1;endend%%%%%%%-------------------------------%%%new_img=zeros(Cha_Zhi_1,Cha_Zhi_2); %%旋转后的新图像的画布大小%%%还没有差值的for i=1:mfor j=1:nnew_img(mm(i,j),nn(i,j))=img(i,j);endendtoc%%%计时结束figure(2);imshow(uint8(new_img));%%%%%% 求对比度%%%%%%function ZhongZhi_filter()clear;clc;[filename,pathname]=uigetfile({'*jpg;*.bmp;*.jpeg'},'load?image');fpath=fullfile(pathname,filename);A=imread(fpath);figure(1);imshow(A);title('原图像')img=rgb2gray(A);figure(2);imshow(img);title('灰度后的');img1=imnoise(img,'salt & pepper',0.05); %加入椒盐躁声figure(3);imshow(img1);title('椒盐后的图像');img2=imnoise(img,'gaussian',0.05); %加入高斯躁声figure(4);imshow(img2);title('高斯噪声后的图像');%%% 以下是中值滤波%%%%%% 中值滤波椒盐噪声%%%AAA=img1; %%%得到椒盐噪声图像[m,n]=size(AAA);for i=2:m-1for j=2:n-1ASD=[AAA(i-1,j-1) AAA(i-1,j) AAA(i-1,j+1) AAA(i,j-1) AAA(i,j) AAA(i,j+1) AAA(i+1,j-1) AAA(i+1,j) AAA(i+1,j)+1];Pai_Xu=sort(ASD);Length=length(Pai_Xu);AAA(i,j)=Pai_Xu((Length+1)/2);endendfigure(7)imshow(AAA);title('中值滤椒盐噪声后的图像');AAA1=img2; %%%得到椒盐噪声图像[m,n]=size(AAA1);for i=2:m-1for j=2:n-1ASD=[AAA1(i-1,j-1) AAA1(i-1,j) AAA1(i-1,j+1) AAA1(i,j-1) AAA1(i,j) AAA1(i,j+1) AAA1(i+1,j-1) AAA1(i+1,j) AAA1(i+1,j+1)];Pai_Xu=sort(ASD); %%%排序Length=length(Pai_Xu); %%%求数组长度AAA1(i,j)=Pai_Xu((Length+1)/2); %%%取最中间的endendfigure(8)imshow(AAA1);title('中值滤高斯噪声后的图像');。