deconv_alm.rar_alm_distributed wavelet _信号 高斯噪声_小波 alm

clear; fid1=fopen('d:/char1.txt','rt'); b=fscanf(fid1,'%d'); sta=fclose(fid1); fid1=fopen('d:/char2.txt','r'); g=fscanf(fid1,'%s'); stb=fclose(fid1); %file=[c,'01.bmp']; %I=imread(file); s={};%m=1;n=9; %if n~=m for i=1 fi=[g,'0' num2str(i) '.bmp']; s{i}=imread(fi); % t{i}=ind2rgb(s{i},map); % s{i}=imread(['c\0' num2str(i) '.bmp']); % m=m+1; % else n=n+9; end %end %end %figure(1),imshow(s{1}); %figure(2),imshow(s{2});figure(3),imshow(s{3});figure(4),imshow(s{4});figure(5),imshow(s{5});figure(6),imshow(s{6}); PicData=[s{1}]; % 横向拼接 imwrite(PicData, 'PicOut.jpg'); % 输出图形 %, 'Quality', 75 %I=PicOut; I=imread('PicOut.jpg'); figure,imshow(I); switch b(1) case 1 %function OstuMethod %最大类间方差法求阈值并二值化（大津法） %clear all threshold = graythresh(I); a=im2bw(I,threshold); figure; imshow(a); title('最大类间方差法处理'); case 2 %function Max_Shang %最大熵法求阈值并二值化 %clear all %s=imread('1_副本.bmp'); % figure,imshow(I) a=rgb2gray(I); count=imhist(a); [m,n]=size(a); N=m*n; L=256; count=count/N;%%每一个像素的分布概率 count for i=1:L if count(i)~=0 st=i-1; break; end end st for i=L:-1:1 if count(i)~=0 nd=i-1; break; end end nd f=count(st+1:nd+1); %f是每个灰度出现的概率 size(f) E=[]; for Th=st:nd-1 %%%设定初始分割阈值为Th av1=0; av2=0; Pth=sum(count(1:Th+1)); %%%第一类的平均相对熵为 for i=0:Th av1=av1-count(i+1)/Pth*log(count(i+1)/Pth+0.00001); end %%%第二类的平均相对熵为 for i=Th+1:L-1 av2=av2-count(i+1)/(1-Pth)*log(count(i+1)/(1-Pth)+0.00001); end E(Th-st+1)=av1+av2; end position=find(E==(max(E))); th=st+position-1 for i=1:m for j=1:n if a(i,j)>th a(i,j)=255; else a(i,j)=0; end end end a=255-a; figure,imshow(a); title('最大熵法处理'); case 3 %function Decide %人工二值化处理 %I=imread('1_副本.bmp'); % figure(1); imshow(I);%显示 % a= rgb2gray(I);%转化为灰度图像 a=I; %figure(2); %imshow(I); J=find(a<b(2)); a(J)=0; J=find(a>=b(2)); a(J)=255; a=255-a; figure; imshow(a); title('图像作人工二值化处理( 域值自定 )'); otherwise,end %se=strel('disk',15); %BW=imclose(BW,se); %figure(2); %imshow(BW); %BW=imfill(BW,[1 1]); %figure(2); %imshow(BW); a=imfill(a,'holes');%填充 %%%极小颗粒及超大面积暗影去除 L = bwlabel(a); mianj=regionprops(L,'Area');%颗粒面积大小 allArea = [mianj.Area]; x = ismember(L, find(8<=[mianj.Area])); L = bwlabel(x); mianj=regionprops(L,'Area');%颗粒面积大小 allArea = [mianj.Area]; x = ismember(L, find([mianj.Area]<=500)); L = bwlabel(x); %颗粒标记 %边缘不完整颗粒去除 D=zeros(size(L)); D([1,end],:)=L([1,end],:); D(:,[1,end])=L(:,[1,end]); [i,j]=find(D~=0); [m,n]=size(i); C=zeros(1,m); for y=1:m C(y)=D(i(y),j(y)); end for y=1:m L(find(L==C(y)))=0; end figure,imshow(L); %L = bwlabel(L); %A=watershed(L); %figure,imshow(A); %加点东西，如果可以的话就要把边沿颗粒去除后的图像显示出来？？？？？？？？？？？？ %T=L; %T(find(T~=0))=1; %imshow(T); duanz=regionprops(L,'MinorAxisLength');%近似为椭圆模型的短轴长 allMinorAxisLength = [duanz.MinorAxisLength]; %hist(allMinorAxisLength);grid on; x=allMinorAxisLength>2; allMinorAxisLength=allMinorAxisLength(x); changz=regionprops(L,'MajorAxisLength');%近似为椭圆模型的长轴长 allMajorAxisLength = [changz.MajorAxisLength]; mianj=regionprops(L,'Area');%颗粒面积大小 allArea = [mianj.Area]; %allArea fangx=regionprops(L,'Orientation');%与X轴的夹角，即运动方向 allOrientation = [fangx.Orientation]; z=sqrt(allArea/pi)*2.0; if length(z)==0 return; end %d=d(find(d>5));% 对很小的粒子忽略 %set(handles.edit1,'string',num2str(mean(z))); %平均直径 %set(handles.edit2,'string',num2str(length(z)));%颗粒个数 %stateMax=regionprops(L,'MajorAxisLength'); %Maxd=[stateMax.MajorAxisLength]; %set(handles.edit6,'string',num2str(mean(Maxd)));%最大粒径 %stateMin=regionprops(L,'MinorAxisLength'); %Mind=[stateMin.MinorAxisLength]; %set(handles.edit7,'string',num2str(mean(Mind)));%最小粒径 %stateCArea=regionprops(L,'ConvexArea'); %ConvexArea=[stateCArea.ConvexArea]; %set(handles.edit8,'string',num2str(mean(ConvexArea))); %stateEDia=regionprops(L,'EquivDiameter'); %EquivDiameter=[stateEDia.EquivDiameter]; %set(handles.edit9,'string',num2str(mean(EquivDiameter))); %stateFArea=regionprops(L,'FilledArea'); %FilledArea=[stateFArea.FilledArea]; %set(handles.edit10,'string',num2str(mean(FilledArea))); %axes(handles.axes1) % Select the proper axes %cla; %imshow(L); %axes(handles.axes2) % Select the proper axes %cla; %hist(z); grid on; %xlabel('不同象素颗粒'); %ylabel('分布 '); %AllResult.size=mean(z); AllResult.num=length(z); %AllResult.z=z; %AllResult.Maxd=Maxd; %AllResult.Mind=Mind; %AllResult.ConvexArea=ConvexArea; %AllResult.EquivDiameter=EquivDiameter; %AllResult.FilledArea=FilledArea; % % % i=get(popupmenu3,'string'); % % % x1=AllResult.d(i); allArea(find(allArea==0))=[];% allOrientation(find(allOrientation==0))=[];% allMajorAxisLength(find(allMajorAxisLength==0))=[];% allMinorAxisLength(find(allMinorAxisLength==0))=[];% fid1=fopen('d:/char3.txt','rt'); d=fscanf(fid1,'%s'); file1=[d,'mji.txt']; file2=[d,'fxiang.txt']; file3=[d,'czhou.txt']; file4=[d,'dzhou.txt']; mji=fopen(file1,'w'); %fprintf(fid,'%f\t%f\n',AllResult.num,AllResult.size); for j=1:length(allArea) fprintf(mji,'%.1f\t%.3f\n',allArea(j)); end fclose(mji); fxiang=fopen(file2,'w'); %fprintf(fid,'%f\t%f\n',AllResult.num,AllResult.size); for j=1:length(allOrientation) fprintf(fxiang,'%.1f\t%.3f\n',allOrientation(j)); end fclose(fxiang); czhou=fopen(file3,'w'); %fprintf(fid,'%f\t%f\n',AllResult.num,AllResult.size); for j=1:length(allMajorAxisLength) fprintf(czhou,'%.1f\t%.3f\n',allMajorAxisLength(j)); end fclose(czhou); dzhou=fopen(file4,'w'); %fprintf(fid,'%f\t%f\n',AllResult.num,AllResult.size); for j=1:length(allMinorAxisLength) fprintf(dzhou,'%.3f\t%.3f\n',allMinorAxisLength(j)); end fclose(dzhou);