数字图像处理上机实验.docx

1、数字图像处理上机实验人民武装学院学生姓名： 周云 学 号： PB102027115专 业: 电子信息科学与技术年 级: 2010 级 扌旨导老师： 陈其松老师 时 间：2011 年12月24日第二章：纸看起一张纸，当放在桌子上时看上去似乎比较白， 当用纸来遮蔽眼睛直视明亮的天空时,来总是黑的 colormap(gray); dark=zeros(256,256); dark(64:192,64:192)=0.5; subplot(1,3,1);imshow(dark) middle(1:256,1:256)=0.7; middle(64:192,64:192)=0.5; subplot(1,3

2、,2);imshow(bright) subplot(1,3,2);imshow(middle) bright=o nes(256,256); bright(64:192,64:192)=0.5; subplot(1,3,3);imshow(bright)1.二值图像 clear x=zeros(10,10); x(2:2:10,2:2:10)=1; imshow(x) x x =Colu mns 1 through 80 0 00 1 00 0 00 1 00 0 00 1 00 0 00 0 01 0 1 0 0 01 0 10 0 01 0 10 0 0000000001010100 1

3、 0101010 0 0000000 1 010101Colu mns 9 through 100 00 10 00 10 00 10 00 10 00 1 d a 鸣札,#圧/l二值图像 2亮度图像： X=imread(D:le na.bmp); imshow(X); Y=X(128:138,128:138); figure,imshow(Y); YY =Colu mns 1 through 81941831731601451271131111861721751711531281121101851781731621451281171141881811681501361281231181921

4、76162145133128125120192165156144135129124119187157152143136130124118181157149139133129125118179159148135129129126118122123172 153 142 130 127 129 129168 151 143 135 133 133 131Colu mns 9 through 11115116116116118118115119120115120120115118118115115115114111112112109110110109110115108112115113115(a)原

5、始图像(b)获取的部分灰度图像 3索引图像： RGB=imread(D:flowers.tif); X,m ap=rgb2i nd(RGB,128); imshow(X,map) X(1)ans =127 X(2)ans =127 map(127,:,:,:) ans =0.7647 0.6118 0.6549 whosName SizeRGB 362x500x3X 362x500ans 1x3Bytes Class543000 uin t8 array 181000 uint8 array24 double array3072 double arraymap 128x3Grand total

6、 is 724387 elements using 727096 bytes索引图像4.RGB图像： X,map=imread(D:xia ngjiao.bmp); Y=X(90:95,90:95); imshow(Y) R=X(90:95,90:95,1); G=X(90:95,90:95,2); B=X(90:95,90:95,3); R,G,BR =175181185189181155171176185188175146171173182186176161171176184186181178170181187186183182170180180181183180175 181 185 1

7、89 181 155171176185188175146171173182186176161171176184186181178170181187186183182170180180181183180B =175181185189181155171176185188175146171173182186176161171176184186181178170181187186183182170180180181183180(a)(b)第三章例3.1把一幅图加上高斯噪声，再通过 100次相加求平均的方法去除噪声l=imread(D:eight.tif); J=im noise(l,gaussia n

8、,0,0.02); subplot(1,2,1),imshow(l); subplot(1,2,2),imshow(J); K=zeros(242,308); for i=1:100J=imno ise(l,gaussia n,0,0.02);J仁 im2double(J);K=K+J1;end K=K/100; figure;imshow(K);(a)原图(b)加噪图(c)求平均后的图例3.3图像的乘法运算:I=imread(D:m oon .tif); J=immultiply(l,1.2); K=immultiply(l,2); subplot(1,3,1),imshow(l); sub

9、plot(1,3,2),imshow(J); subplot(1,3,3),imshow(K);|li Ik.- fin .taraa Irili tawi分别为：原图、乘以 1.2、乘以2例3.4除法运算moon=imread(m oon .tif); I=double(m oon); J=l*0.43+90; K=I*0.1+90; L=l*0.01+90; moon2=uin t8(J); moo n3=ui nt8(K); moon4=uin t8(L); J=imdivide(m oon,moon 2); K=imdivide(m oon,moon 3);L=imdivide(m o

10、on,moon 4); subplot(2,2,1),imshow(m oon); subplot(2,2,2),imshow(J,); subplot(2,2,3),imshow(K,); subplot(2,2,4),imshow(L,);分别为：原图、 J=l*0.43+90、K=l*0.1+90、L=l*0.01+90例3.5逻辑运算: l=imread(D:m oon .tif); A=zeros(128); A(40:67,60:100)=1; figure(1); imshow(A); B=zeros(128); B(50:80,40:70)=1; figure(2); imsh

11、ow(B); C=a nd(A,B); figure(3); imshow(C); D=or(A,B); figure(4); imshow(D); E=not(A); figure(5);(a) A 图(b) B 图(c)A、B相与结果图(d)A、B相或结果图(c)A取反结果图例3.6实现把一副图像旋转 60度，并分别采用把转出显示区域的图像截去和扩大显示区域范围以显示图像的全部两种方式 l=imread(D:9.jpg); J=imrotate(l,60,bili nea。； imshow(J); K=imrotate(I,60,bili near,crop); imshow(K); I=

12、imread(D:9.jpg); J=imrotate(I,60,bili nea。； K=imrotate(I,60,bili near,crop); subplot(1,3,1),imshow(I); subplot(1,3,2),imshow(J); subplot(1,3,3),imshow(K);分别为：原图、旋转图（部分）、旋转图（全部）例3.7采用三种不同插值法进行图片的放大比较: I=imread(D:le na.jpg); J1=imresize(I,10, nearest); J2=imresize(I,10,bili nea。； J3=imresize(l,10,bicu

13、bic); figure imshow(I); title(原图); figure imshow(J1); title(最近邻法); figure imshow(J2); title(双线性插值法); figure imshow(J3); title(三次内插法);第四章例4.2图像的二维离散傅里叶频谱: l=imread(D:i nst_bkgr nd.bmp); imshow(I) J=fftshift(fft2(I); figure(2); imshow(log(abs(J),8,10)(a)原始图像(b)散傅里叶频谱例4.4二维离散傅里叶变换的旋转性： l=zeros(256,256)

14、; 1(28:228,108:148)=1; imshow(I) J=fft2(I); F=abs(J); J1=fftshift(F);figure imshow(J1,5 50) I=zeros(256,256); | 1(28:228,108:148)=1; J=imrotate(I,315,bili near,crop); figure imshow(J) J1=fft2(J); F=abs(J1); J2=fftshift(F);figure imshow(J2,5 50)(a)原始图像(b)原图像的傅里叶频谱(c)旋转后的图像(d)旋转后图像的傅里叶频谱例4.5比例尺度展宽： cl

15、ear; l=zeros(256,256); 1(8:248,110:136)=5; figure imshow(I) a=0.1; J3=fft2(I); F2=abs(J3); J4=fftshift(F2); figure(2) imshow(J4,5 30) for i=1:256for j=1:256I(i,j)=I(i,j)*a;endend J2=fft2(I); F1=abs(J2); J3=fftshift(F1); figure(3) imshow(J3,5 30)a a.(a)原始图像(b)比例尺度展宽前的频谱(c)比例尺度a=0.1,b=1,展宽后的频谱例4.7 (a)

16、图乘以一指数，将图像亮度整体变暗，并求其中心移到零点的频谱图 l=imread(D:in st_bkgr nd.bmp); figure(1); imshow(I) P=l& exp(-1); figure(2); imshow(P) P仁 fftshift(fft2(P); figure(3); imshow(log(abs(P1),8,10)(a)原图(b)变暗后的图(c)中心移到零点的频谱图例4.8 (a)加入高斯噪声，得出一个有颗粒噪声的图，并求其中心移到零点的频谱图。 l=imread(D:/cs_assault.bmp); l=imno ise(l,gaussia n,0,0.01

17、); figure; imshow(I); P=fftshift(fft2(I); figure; imshow(log(abs(P),8,10)(a)原图(b)有颗粒噪声(c)有颗粒噪声中心移到零点的频谱图例4.9 l=imread(E:img4.bmp); figure imshow(real(I); I=I(:,:,3); fftI=fft2(I); sfftl=fftshift(fftl); RRfdp仁real(sfftl); Ilfdp1=imag(sfftl); a=sqrt(RRfdp1.A2+llfdp1.A2); a=(a-mi n( mi n( a)/(max(max(a

18、)-mi n( mi n(a)*225; figure(2) imshow(real(a); b=a ngle(fftl); figure(3) imshow(real(b); theta=30; RR1=a*cos(theta); II1=a*s in( the ts); II1= a*s in (theta); fftl 1=RR1+i.*II1; C=ifft2(fftI1)*225; figure(4) imshow(real(C); MM=150; RR2=MM*cos(a ngle(fftl); II2=MM*si n(an gle(fftl); fftI2=RR2+i.*II2;

19、 D=ifft2(fftI2); figure(5) imshow(real(D);(a)幅值普(b)相位谱(c)幅值谱重构图像(d)相位谱重构图像例4.10说明二维余弦正反变换在 MATLAB中的实现:RGB=imread( i_lean.tif);l=rgb2gray(RGB);Imshow(l);Figure(2);J=dct2(l);imshow(log(abs(J),);Figure(3);J(abs(J) figure,imshow(I);title(orig inal image); J=imcompleme nt(l); figure,imshow(J);title( nega

20、tive image);LI 11 舍禹 2# *MW 心血3T*nhxI a t： Mi* T丄 A t 二即 “ MU A H $ !$/ !：.例5.3对灰度图像进行均衡化，灰度等级为 8级: 匸imread(D:le na.jpg); 匸rgb2gray(l); K=16; H=histeq(l,K); figure,subplot(2,2,1),imshow(l,); subplot(2,2,2),imshow(H,),hold on subplot(2,2,3),hist(double(l),16),subplot(2,2,4),hist(double(H),16)L t! ! +

21、例5.4对图像进行平滑Img=rgb2gray(imread( D:/lmage.bmp 7);Figure;imshow(img);img_noise=double(imnoise(img, salt&pepper ,0.06); figure,imshow(img_ no ise,);img_smoothed=imfilter(img_ no ise,fspecial( average ,5); figure;imshow(img_smoothed,);(a)原图像(b)加椒盐噪声的图像(c)平滑第八早 例6.1l=imread(H:img2.bmp); figure,imshow(l),

22、figure,hist(double(l),10) J=imno ise(l,gaussia n,0.05); figure,imshow(J),figure,hist(double(J),10) J=imno ise(l,speckle,0.05); figure,imshow(J),figure,hist(double(J),10) J=imno ise(l,salt & pepper,0.05); figure,imshow(J),figure,hist(double(J),10)11- I*1 z- A S - Hv k ? i- (a)原图(b)高斯噪声图(c)均匀分布噪声P* F-

23、子-I- I1-*- HUD-U# k k Jf -(d)椒盐噪声例6.2img=imread(H:img2.bmp); figure;imshow(img); img_ no ise=double(i mno ise(img,gaussia n,0.06); figure,imshow(img_ no ise,); img_mea n=i mfilter(img_ no ise,fspecial(average,3); figure;imshow(img_mean,);title(de_noise by mean filter); img_mea n=exp()imfilter(log(img_ no ise),fspecial(average,3);- *(a)输入图像(b)高斯噪声污染图像(c)用均值滤波结果(d)几何均值滤波(e) Q=- 1.5的逆谐波滤波(f) Q=1.5滤波的结果