作業(yè)11. 用matlab程序?qū)崿F(xiàn)同時對比度實驗。程序代碼如下:clear m=256; n=256; ground_gray1=200; X1=ones(m,n)*ground_gray1; ground_gray2=100; X2=ones(m,n)*ground_gray2; before_gray=150; m0=100; n0=100; step=50; X1(m0:m0+step,n0:n0+step)=before_gray; figure; imshow(uint8(X1); X2(m0:m0+step,n0:n0+step)=before_gray; figure; imshow(uint8(X2); 得到的圖像如下： 2. 用matlab程序?qū)嶒灴臻g分辨率變化效果。程序代碼如下:clear X=imread(picture1.jpg); figure; imshow(uint8(X); m,n=size(X); X1=X(1:2:m,1:2:n); figure; imshow(uint8(X1); imwrite(X1,picture1.jpg); 得到的圖形如下3. 用matlab程序?qū)嶒灧确直媛首兓Ч?程序代碼如下：clearX=imread(picture1.jpg);mm,nn=size(X);for i=1:mm for j=1:nn X128(i,j)=2*(ceil(X(i,j)/2); endendfor i=1:mm for j=1:nn X64(i,j)=4*(ceil(X(i,j)/4); endend for i=1:mm for j=1:nn X32(i,j)=8*(ceil(X(i,j)/8); endend figuresubplot(2,2,1);imshow(uint8(X);title(256級);subplot(2,2,2);imshow(uint8(X128);title(128級);subplot(2,2,3);imshow(uint8(X64);title(64級);subplot(2,2,4);imshow(uint8(X32);title(32級);得到的圖像如下作業(yè)21. 用matlab作出圖像的直方圖。程序代碼如下：clear;A = imread(picture2.jpg);I = rgb2gray(A);add = ;tab1 = zeros(1,256);for n = 0:255; X = I = n; add = add; sum(sum(X);end;a, b = size(I);final = add / (a*b);figure;stem(final, Marker, none);figure(2);imshow(I);得到的圖像如下2. 用matlab實現(xiàn)圖像的直方圖均衡化程序代碼如下:clear allm=imread(picture2.jpg);A = rgb2gray(m); m,n=size(A);B=zeros(size(A);l=m*n;r=zeros(1,256);y=zeros(1,256);A=double(A);for i=1:mfor j=1:n r(A(i,j)+1)=r(A(i,j)+1)+1;endendr=r./l;for k=1:256for j=1:ky(k)=y(k)+r(j);endend for k=1:256 y(k)=floor(255*y(k)+0.5); endfor i=1:mfor j=1:nB(i,j)=y(A(i,j)+1);endendA=uint8(A);B=uint8(B);subplot(2,2,1)imshow(A)title(原圖像)subplot(2,2,2)imhist(A)title(原圖像的直方圖)subplot(2,2,3)imshow(B)title(經(jīng)過均衡處理的圖像)subplot(2,2,4)imhist(B)title(經(jīng)過均衡處理后該圖像的直方圖)得到的圖像如下作業(yè)31. 用 matlab實現(xiàn)多幅圖像平均去高斯白噪聲。程序代碼如下：clear; A=imread(picture2.jpg); I=rgb2gray(A); imshow(I); a,b=size(I); noise=randn(a,b)*30; X=double(I)+noise; Y=zeros(a,b); figure(2); imshow(uint8(X); for n=1:30 noise=randn(a,b)*30; X=double(I)+noise; Y=Y+double(X); end; Y=Y/n; figure(3); imshow(uint8(Y)得到的圖像如下：原圖加了高斯白噪聲的圖像：去噪后的圖像:2. 用 matlab實現(xiàn)均值濾波去除高斯白噪聲.程序代碼如下：clear; A=imread(picture2.jpg); I=rgb2gray(A); figure; imshow(I); a,b=size(I); noise=randn(a,b)*30; I=double(I)+noise; I2=zeros(a+2,b+2); I3=zeros(a,b); for n=1:a for m=1:b I2(n+1,m+1)=I(n,m); end; end;figure(2);imshow(uint8(I2); for n=2:a for m=2:b I3(n-1,m-1)=I2(n-1,m-1)+I2(n-1,m)+I2(n-1,m+1)+I2(n,m-1)+I2(n,m)+I2(n,m+1)+I2(n+1,m-1)+I2(n+1,m)+I2(n+1,m+1)/9; end; end;figure(3);imshow(uint8(I3);得到的圖像如下：原圖加高斯白噪聲圖像均值濾波去噪后圖像3. 用 matlab實現(xiàn)中值濾波去除脈沖噪聲。程序代碼如下：clear; A=imread(picture2.jpg); I=rgb2gray(A); figure(1); imshow(I); X=zeros(1:9); a,b=size(I); Y=zeros(a+2,b+2); Z=zeros(a,b); for n=1:a for m=1:b Y(n+1,m+1)=I(n,m); end; end; for n=0:100 Y(round(rand*a),round(rand*b)=0; end;for n=0:200 Y(round(rand*a),round(rand*b)=255; end; figure(2) imshow(uint8(Y); Y=double(Y); for n=2:a for m=2:b X=Y(n-1,m-1),Y(n-1,m),Y(n-1,m+