matlab數(shù)字圖像處理源代碼

精心整理數(shù)字像去典型法及matlab現(xiàn)希望到大的指和幫鹽維使原始圖實(shí)驗(yàn)：I=imread('C:\DocumentsandSettings\Administrator\桌面\1.gif');%取像J=imnoise(I,'gaussian',0,0.005);%入值方差0.005的斯聲subplot(2,3,1);imshow(I);title('始圖);

精心整理subplot(2,3,2);imshow(J);title('入高噪之的像'%用MATLAB中的數(shù)filter2受聲干的像行值波K1=filter2(fspecial('average',3),J)/255;%模尺為K2=filter2(fspecial('average',5),J)/255;%模尺為K3=filter2(fspecial('average',7),J)/255;%模尺為K4=filter2(fspecial('average',9),J)/255;%模尺為subplot(2,3,3);imshow(K1);title('進(jìn)后圖');subplot(2,3,4);imshow(K2);title('進(jìn)后圖');subplot(2,3,5);imshow(K3);title('進(jìn)后圖');subplot(2,3,6);imshow(K4);title('進(jìn)后圖');PS：用法：用

fspecialn[[0.5。

精心整理type='laplacian'[0,1]0type='log'，為拉[.5type='prewitt'算子的算子type='unsharp'，[0,1]據(jù)我測，用均濾波噪（噪聲效果用的域半越大果越，當(dāng)其代也會更，另確切去噪果的還需用等數(shù)據(jù)來度。實(shí)驗(yàn)：二自適維納波對噪聲濾除果I=imread('C:\DocumentsandSettings\Administrator\桌面\1.gif');%取像J=imnoise(I,'gaussian',0,0.005);%入值方差0.005的斯聲K2=wiener2(J,[33]);%對加圖進(jìn)二自應(yīng)納濾K2=wiener2(J,[55]);%對加圖進(jìn)二自應(yīng)納濾K2=wiener2(J,[77]);%對加圖進(jìn)二自應(yīng)納濾K2=wiener2(J,[99]);%對加圖進(jìn)二自應(yīng)納濾subplot(2,3,1);imshow(I);title('始圖);subplot(2,3,2);imshow(J);title('噪圖);subplot(2,3,3);imshow(K1);title('復(fù)圖1subplot(2,3,4);imshow(K2);

精心整理title('復(fù)圖2subplot(2,3,5);imshow(K3);title('復(fù)圖3subplot(2,3,6);imshow(K4);title('復(fù)圖3PS維納濾波的兩個函數(shù)與deconvwnr都夠完成納濾波的功能調(diào)圖象復(fù)原方面強(qiáng)調(diào)圖象空間域銳化的作用，其中J=wiener2(I,[m,n])回有噪聲圖像經(jīng)wierner(維濾后的圖像指定濾波器窗口大小為m*n,默認(rèn)值為3*3J=wiener2(I,[m,n],noise)定噪聲的功率，[J,noise]=wiener2(I,[m,n])在圖像濾波的同時，返回噪聲功率的估計(jì)值noise維納濾波的兩個函數(shù)與deconvwnr都夠完成維納濾波的功能deconvwnr強(qiáng)圖象復(fù)原方面，強(qiáng)調(diào)圖象空間域銳化的作用，其中J=wiener2(I,[m,n])回有噪聲圖像經(jīng)wierner(維濾后的圖像指定濾波器窗口大小為m*n,默認(rèn)值為3*3J=wiener2(I,[m,n],noise)定噪聲的功率，[J,noise]=wiener2(I,[m,n])在圖像濾波的同時，返回噪聲功率的估計(jì)值。

imnoise的語法式為J=imnoise(I,type)J=imnoise(I,type,parameters)其中J=imnoise(I,type)返原始像I典型聲的噪圖J參數(shù)typeparameters定噪的類和相的參。下面命令對圖像.gif加入斯噪、椒噪聲乘性聲，結(jié)果實(shí)驗(yàn)：對入椒噪聲圖像作均、中和維濾波I=imread(1.gif');J1=imnoise(I,'gaussian',0,0.02);J2=imnoise(I,'salt&pepper',0.02);J3=imnoise(I,'speckle',0.02);運(yùn)效見2I=imread('C:\DocumentsandSettings\Administrator\桌面\1.gif');J=imnoise(I,'salt&pepper',0.02);%h=ones(3,3)/9;%產(chǎn)生3*3的1數(shù)

精心整理%B=conv2(J,h);%卷積算K2=filter2(fspecial('average',3),J)/255;%均濾模板寸K=medfilt2(J);%采用二中濾函medfilt2對椒噪干的圖濾K1=wiener2(J,[33]);%對加圖進(jìn)二自應(yīng)納濾subplot(2,3,1);imshow(I);title('始圖);subplot(2,3,2);imshow(J);title('噪圖);subplot(2,3,3);imshow(K2);title('值濾后圖');subplot(2,3,4);imshow(K);title('值濾后圖');subplot(2,3,5);imshow(K1);title('納濾后圖');PS：MATLAB中供了卷積運(yùn)算的函數(shù)命令，其語格式為：：MATLAB中提供了卷積運(yùn)算的函數(shù)命令conv2，語法格式為：返和C?！羘a×nbC(ma+mb+1)(na+nb+1)MATLAB圖處理具箱供了于卷的圖濾波數(shù)filter2，filter2的法格為：Y=filter2(h,X)其中Y=filter2(h,X)圖像X經(jīng)算h的結(jié)默回圖Y與輸圖像X大小相。例如

精心整理其實(shí)filter2conv2是等價MATLAB在計(jì)算filter2先將積核轉(zhuǎn)180度調(diào)用conv2函數(shù)行計(jì)。Fspecial數(shù)用創(chuàng)建定義濾波子，語法式為h=fspecial(type)h=fspecial(type,parameters)參數(shù)type子類，parameters指定的參，具格式前文有敘。ones全1數(shù)組，zeros全零組。ones(a,b)產(chǎn)生a行b列全1組ones(a)a行a列全數(shù)通過3我也可出結(jié)，即值濾于去椒鹽聲效最好而維濾波除效則較差中值波對去除鹽噪果明，是為椒噪聲在畫上的分點(diǎn)機(jī)出，而中濾波據(jù)數(shù)排序?qū)⑽慈镜拇媛朁c(diǎn)值的率較，所抑制果好對點(diǎn)、和尖較多圖像宜采值濾，因一些節(jié)點(diǎn)能被成噪點(diǎn)。實(shí)驗(yàn):分使用維統(tǒng)濾波椒鹽聲和斯噪進(jìn)行波I=imread('C:\DocumentsandSettings\Administrator\桌面\1.gif');J1=imnoise(I,'salt&pepper',0.004);subplot(2,3,1);imshow(I);title('始圖);subplot(2,3,2);imshow(J1);title('椒鹽聲的像);J=ordfilt2(J1,5,ones(3,4));%行維計(jì)序?yàn)Vsubplot(2,3,3);imshow(J);title('鹽噪濾后圖');J2=imnoise(I,'gaussian',0,0.004);subplot(2,3,4);imshow(J2);

精心整理title('高斯聲的像);J3=ordfilt2(J2,5,ones(3,4));subplot(2,3,5);imshow(J3);title('斯噪濾后圖');PS:PS：MATLAB小波分工具提供用于像去的函有wrcoef2和wpdencmp其語格式分為：X=wrcoef2(‘type’,C,S,’wname’[xd,treed,datad,perf0,perfl2]=wpdencmp(x,sorh,N,’wname’,crit,par,keepapp)其中X=wrcoef2(type’wname)基于波分結(jié)構(gòu)Ｃ，］的重構(gòu)像Ｘ。數(shù)“type”a示重近似數(shù)；于h表重構(gòu)平細(xì)系數(shù)等于v示重垂直節(jié)系，等d示重對角節(jié)系。[xd,treed,datad,perf0,perfl2]=wpdencmp(x,sorh,N,’wname’,crit,par,keepapp)是過小包定限（值化，回輸信號圖像的除結(jié)果xd。輸入數(shù)中［treed,datadxd最佳小包分結(jié)構(gòu)；perfl2perf0表示L^2復(fù)和壓百分perf12=100*(xd波包向量數(shù)/X小波包系向量數(shù))示近似系不能值化否以閾化；sorh=’s為閾值，h硬閾化。實(shí)驗(yàn)：利wrcoef2數(shù)進(jìn)圖像噪其程代碼下：I=imread('C:\DocumentsandSettings\Administrator\桌面\1.gif');J=imnoise(I,'gaussian',0,0.005);[c,l]=wavedec2(J,2,'sym4');J1=wrcoef2('a',c,l,'sym4',1);

精心整理J2=wrcoef2('a',c,l,'sym4',2);subplot(2,2,1);imshow(I);title('始圖);subplot(2,2,2);imsho