数字图像处理

1、1.对自己的头像进行操作，分别比较保留10,20,40个DCT变换系数重构的图像与原始图像进行操作。clear all; I=rgb2gray(imread(.jpg);J=im2double(I);T=dctmtx(8);K=blkproc(J, 8 8, P1*x*P2, T, T); mask1= 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ;K1=blkproc(K, 8 8,

2、 P1.*x, mask1);L1=blkproc(K1, 8 8, P1*x*P2, T, T);figure;subplot(221);imshow(J);subplot(222);imshow(L1); mask2= 1 1 1 1 1 1 0 0 1 1 1 1 1 0 0 0 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ;K2=blkproc(K, 8 8, P1.*x, mask2);L2=blkproc(K2, 8 8, P1*x*P

3、2, T, T);subplot(223);imshow(L2); mask2= 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1 0 0 0 1 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 ;K3=blkproc(K, 8 8, P1.*x, mask2);L3=blkproc(K3, 8 8, P1*x*P2, T, T);subplot(224);imshow(L3);2.1I=rgb2gray(imread(.jpg);I=im2double

4、(I)*255;height,width=size(I); %求图像的大小HWmatrix=zeros(height,width);Mat=zeros(height,width); %建立大小与原图像大小相同的矩阵HWmatrix和Mat，矩阵元素为0。HWmatrix(1,1)=I(1,1); %图像第一个像素值I(1,1)传给HWmatrix(1,1)for i=2:height %以下将图像像素值传递给矩阵Mat Mat(i,1)=I(i-1,1);endfor j=2:width Mat(1,j)=I(1,j-1);endfor i=2:height for j=2:width Mat

5、(i,j)=I(i,j-1)/2+I(i-1,j)/2; endendMat=floor(Mat);HWmatrix=I-Mat;SymPro=zeros(2,1); SymNum=1; SymPro(1,1)=HWmatrix(1,1); SymExist=0;for i=1:height for j=1:width SymExist=0; for k=1:SymNum if SymPro(1,k)=HWmatrix(i,j) SymPro(2,k)=SymPro(2,k)+1; SymExist=1; break; end end if SymExist=0 SymNum=SymNum+1

6、; SymPro(1,SymNum)=HWmatrix(i,j); SymPro(2,SymNum)=1; end endendfor i=1:SymNum SymPro(3,i)=SymPro(2,i)/(height*width);endsymbols=SymPro(1,:);p=SymPro(3,:);dict,avglen = huffmandict(symbols,p); %产生霍夫曼编码词典，返回编码词典dict和平均码长avglenactualsig=reshape(HWmatrix,1,);compress=huffmanenco(actualsig,dict); %利用dic

7、t对actuals来编码，其结果存放在compress中UnitNum=ceil(size(compress,2)/8); Compressed=zeros(1,UnitNum,uint8);for i=1:UnitNum for j=1:8 if (i-1)*8+j)=size(compress,2) Compressed(i)=bitset(Compressed(i),j,compress(i-1)*8+j); end endendNewHeight=ceil(UnitNum/512);Compressed(width*NewHeight)=0;ReshapeCompressed=resh

8、ape(Compressed,NewHeight,width);imwrite(ReshapeCompressed,Compressed Image.bmp,bmp);Restore=zeros(1,size(compress,2);for i=1:UnitNum for j=1:8 if (i-1)*8+j)=size(compress,2) Restore(i-1)*8+j)=bitget(Compressed(i),j); end endenddecompress=huffmandeco(Restore,dict); RestoredImage=reshape(decompress,51

9、2,512);RestoredImageGrayScale=uint8(RestoredImage+Mat);imwrite(RestoredImageGrayScale,Restored Image.bmp,bmp);figure;subplot(1,3,1);imshow(I,0,255); %显示原图subplot(1,3,2);imshow(ReshapeCompressed); %显示压缩后的图像subplot(1,3,3);imshow(Restored Image.bmp); %解压后的图像2.2J=rgb2gray(imread(.jpg); X=im2double(J);Y=

10、LPCencode(X);XX=LPCdecode(Y);figure(1),subplot(121);imshow(J);subplot(122),imshow(mat2gray(255-Y); %为方便显示，对预测误差图取反后再作显示e=double(X)-double(XX);m,n=size(e);erm=sqrt(sum(e(:).2)/(m*n); figure(2);h,x=hist(X(:);%得到原图直方图subplot(121);bar(x,h,k);%显示原图像的直方图h,x=hist(Y(:);%得到预测误差的直方图subplot(122);bar(x,h,k);%显示

11、预测误差的直方图%LPCdecode是解码程序，与编码程序用的是同一个预测器function x=LPCdecode(y,f)error(nargchk(1,2,nargin);if nargin2 f=1;endf=f(end:-1:1);m,n=size(y);order=length(f);f=repmat(f,m,1);x=zeros(m,n+order);for j=1:n jj=j+order; x(:,jj)=y(:,j)+round(sum(f(:,order:-1:1).*x(:,(jj-1):-1:(jj-order),2);endx=x(:,order+1:end);%LPCencode 函数用一维预测编码压缩图像x,f为预测系数，如果f去默认值，则默认f=1,就是前值预测function y=LPCencode(x,