MATLAB图像处理工具箱函数讲课讲稿

1、Good is good, but better carries it.精益求精，善益求善。MATLAB图像处理工具箱函数-表A-1通用函数函数功能语法Colorbar显示颜色条colorbarcolorbar(Vert)colorbar(horiz)colorbar(h_h=colorbar()colorbar(,peer,axes_handle)Getimage从坐标轴取得图形数据A=getimage(h)x,y,A=getimage(h),A,flag=getimage(h)=getimageImshow显示图像Imshow(I,n)Imshow(I,lowhigh)Imshow(BW)

2、Imshow(X,map)Imshow(RGB)Imshow(,display_option)Imshow(x,y,A,)ImshowfilenameH=Imshow()Montage在矩形框中同时显示多幅图像montage（I）montage(BW)montage(X,map)montage(RGB)h=montage()Immovie创建多帧索引色图像的电影动画mov=immovie(X,map)mov=immovie(RGB)Subimage在一幅图中显示多个图像Subimage(X,map)Subimage(I)Subimage(BW)Subimage(RGB)Subimage(x,y

3、,)H=subimage()Truesize调整图像显示尺寸Truesize(fig,mrowsmcols)Truesize(fig)Warp将图像显示到纹理映射表面Warp(X,map)Warp(I,n)Warp(z,)Warp(x,y,z,)H=warp()Zoom缩放图像ZoomonZoomoffZoomoutZoomresetzoomzoomxonzoomyonzoom(factor)zoom(fig,option)表A-2几何操作函数函数功能语法Imcrop剪切图像I2=imcrop(I)X2=imcrop(X,map)RGB2=imcrop(RGB)I2=imcrop(I,rect

4、)RGB2=imcrop(RGB,rect)=imcrop(x,y,)A,rect=imcrop()x,y,A,rect=imcrop()Imresize改变图像大小B=imresize(A,m,method)Imrotate旋转图像B=imrotate(A,angel,method)B=imrotate(A,angel,method,crop)表A-3图像文件I/O函数函数功能语法Imfinfo返回图形文件信息Info=imfinfo(filename,fmt)Info=imfinfo(filename)Imread从图形文件中读取图像A=imrea(filename,fmt)X,map=i

5、mrea(filename,fmt)=imread(filename)=imread(URL,)=imread(idx)(CUR,ICO,andTIFFonly)=imread(,frames,idx)(GIFonly)=imread(,ref)(HDFonly)=imread(,backGrounColor,BG)(PNGonly)A,map,alpha=imread()(ICO,CURandPNGonly)Imwrite把图像写入图形文件中Imwrite(A,filename,fnt)Imwrite(X,map,filename,fmt)Imwrite(,filename)Imwrite(

6、,Param1,Val1,Param2,Val2,)表A-4线性滤波函数函数功能语法Conv2进行二维卷积操作C=conv2(A,B)C=conv2(hcol,hrow,A)C=conv2(,shape)Convmtx2计算二维卷积矩阵T=convmtx2(H,m,n)T=convmtx2(H,m,n)Convn计算n维卷积C=convn(A,B)C=convn(A,B,shape)Filter2进行二维线性过滤操作Y=filter2(h,x)Y=filter2(h,X,shape)Fspecial创建预定义过滤器H=fspecial(type)H=fspecial(type,paramete

7、rs)表A-5像素和统计处理函数函数功能语法Corr2计算两个矩阵的二维相关系数R=corr2(A,B)Imcontour创建图像数据的轮廓图Imcontour(I,n)Imcontour(I,v)Imcontour(x,y,)Imcontour(,lineSpec)C,h=imcontour()Imfeature计算图像区域的特征尺寸Stats=imfeature(L,measurements)Stats=imfeature(L,measurements,n)Imhist显示图像数据的柱状图Imhist(I,n)Imhist(X,map)count,X=imhist()Impixel确定像素

8、颜色值P=impixel(I)P=impixel(X,map)P=impixel(RGB)P=impixel(I,c,r)P=impixel(X,map,C,r)P=impixel(RGB,c,r)c,r,P=impixel()P=impixel(x,y,I,xi,yi)P=impixel(x,y,X,map,xi,yi)P=impixel(x,y,RGB,xi,yi)xi,yi,P=impixel(x,y,)Improfile沿线段计算剖面图的像素值C=improfileC=improfile(n)C=improfile(I,xi,yi)C=improfile(I,xi,yi,n)cx,cy

9、,c=improfile()cx,cy,c,xi,yi=improfile()=improfile(x,y,I,xi,yi,)=improfile(x,y,I,xi,yi,n)=improfile(，method)Mean2计算矩阵元素的平均值B=mean2(A)Pixval显示图像像素信息PixvalonStd2计算矩阵元素的标准偏移B=std2(A)表A-6图像增强函数函数功能语法Histeq用柱状图均衡化增强对比J=histeq(I,hgram)J=histeq(I,n)J,T=histeq(I,)Newmap=histeq(X,map,hgram)Newmap=histeq(X,map

10、)newmap,T=histeq(X,)Imadjust调整图像灰度值或颜色映射表J=imadjust(I,low_inhigh_in,low_outhigh_out,gamma)Newmap=imadjust(map,low_inhigh_in,low_outhigh_out,gamma)RGB2=imadjust(RGB1,)Imnoise增强图像渲染效果J=imnoise(I,type)J=imnoise(I,type,parameters)Medfilt2进行二维中值过滤B=medfilt2(A,m,n)B=medfilt2(A)B=medfilt2(A,indexed,)Ordfil

11、t2进行二维统计顺序过滤B=ordfilt2(A,order,domain)B=ordfilt2(A,order,domain,S)B=ordfilt2(,padopt)Wiener2进行二维适应性去噪过滤处理J=wiener2(I,m,n,noise)J,noise=wiener2(I,m,n)表A-7图像分析函数函数功能语法Edge识别强度图像中的边界BW=edge(I,sobel)BW=edge(I,sobel,thresh)BW=edge(I,sobel,thresh,direction)BW,thresh=edge(I,sobel,)BW=edge(I,prewitt)BW=edge

12、(I,prewitt,thresh)BW=edge(I,prewitt,thresh,direction)BW,thresh=edge(I,prewitt,)BW=edge(I,roberts)BW=edge(I,roberts,thresh)BW,thresh=edge(I,roberts,)BW=edge(I,log)BW=edge(I,log,thresh)BW=edge(I,log,thresh,sigma)BW,thresh=edge(I,log,)BW=edge(I,zerocross,thresh,h)BW,thresh=edge(I,zerocross,)BW=edge(I,c

13、anny)BW=edge(I,canny,thresh)BW=edge(I,canny,thresh,sigma)BW,threshold=edge(I,canny,)Qtgetblk获取四叉树中的块值vals,r,c=qtgetblk(I,S,dim)vals,idx=qtgetblk(I,S,dim)Qtsetblk设置四叉树中的块值J=qtsetblk(I,S,dim,vals)表A-8线性二维滤波设计函数函数功能语法Frespace确定二维频率响应频率空间f1,f2=freqspace(n)f1,f2=freqspace(m,n)x1,y1freqspace(,meshgrid)F=f

14、reqspace(N)F=freqspace(N,whole)Freqz2计算二维频率响应H,f1,f2=freqz2(h,n1,n2)H,f1,f2=freqz2(h,n2,n1)H,f1,f2=freqz2(h,f1,f2)H,f1,f2=freqz2(h)=freqz2(h,dx,dy)=freqz2(h,dx)Freqz2()Fsamp2用频率采样法设计二维FIR过滤器H=fsamp2(Hd)H=fsamp2(f1,f2,Hd,m,n)Ftrans2通过频率转换设计二维FIR过滤器H=ftrans2(b,t)H=ftrans2b)Fwind1用一维窗口法设计二维FIR过滤器H=fwin

15、d1(Hd,win)H=fwind1(Hd,win1,win2)H=fwind1(f1,f2,Hd,)Fwind2用二维窗口法设计二维FIR过滤器H=fwind2(Hd,win)H=fwind2(f1,f2,Hd,win)表A-9二进制图像操作函数函数功能语法Applylut在二进制图像中利用lookup表进行边沿操作A=applylut(BW,LUT)Bwarea计算二进制图像对象的面积Total=bwarea(BW)Bweuler计算二进制图像的欧拉数Eul=bweuler(BW,n)Bwfill填充二进制图像的背景Bw2=bwfill(BW1,c,r,n)BW2=bwfill(BW1,n

16、)BW2,idx=bwfill()BW2=bwfill(x,y,BW1,xi,yi,n)x,y,BW2,idx,xi,yi=bwfill()BW2=bwfill(BW1,holes,n)BW2,idx=bwfill(BW1,holes,n)Bwlabel标注二进制图像中已连接的部分L=bwlabel(BW,n)L,num=bwlabel(BW,n)Bwmorph提取二进制图像的轮廓BW2=bwmorph(BW1,operation)BW2=bwmorph(BW1,operation,n)Bwperim计算二进制图像中对象的周长BW2=bwperim(BW1)bW2=bwperim(BW1,CO

17、NN)Bwselect在二进制图像中选择对象BW2=bwselect(BW1,c,r,n)BW2=bwselect(BW1,n)BW2,idx=bwselect()BW2=bwselect(x,y,BW1,xi,yi)x,y,BW2,idx,xi,yi=bwselect()Dilate放大二进制图像BW2=dilate(BW1,SE)BW2=dilate(BW1,SE,lag)BW2=dilate(BW1,SE,n)Erode弱化二进制图像的边界BW2=erode(BW1,SE)BW2=erode(BW1,SE,lag)BW2=erode(BW1,SE,n)Makelut创建一个用于apply

18、lut()函数的look表Lut=makelut(fun,n)Lut=makelut(fun,n,P1,P2,)表A-10图像变换函数函数功能语法Dct2进行二维离散余弦变换B=dct2(A)B=dct2(A,m,n)B=dct2(A,m,n)Dctmtx计算离散余弦变换矩阵D=dctmtx(n)Fft2进行二维快速傅立叶变换Y=fft2(X)Y=fft2(X,m,n)Fftn进行n维快速傅立叶变换Y=fftn(X)Y=fftn(X,size)Fftshift把快速傅立叶变换的DC组件移到光谱中心Y=fftshift(X)Y=fftshift(X,dim)Idct2计算二维离散反余弦变换B=i

19、dct2(A)B=idct2(A,m,n)B=idct2(A,m,n)Ifft2计算二维快速傅立叶反变换Y=ifft2(X)Y=ifft2(X,m,n)Ifftn计算n维快速傅立叶反变换Y=ifftn(X)Y=ifftn(X,size)Iradon进行反radon变换I=iradon(P,theta)I=iradon(P,theta,interp,filter,d,n)I,h=iradon()Phantom产生一个头部幻影图像P=phantom(def,n)P=phantom(E,n)P,E=phantom()Radon计算randon变换R=radon(I,theta)R,xp=radon(

20、)表A-11颜色空间转换函数函数功能语法Hsv2rgb转换HSV的值为RGB颜色空间M=hsv2rgb(H)Rgb2hsv转化RGB的值为HSV颜色空间Cmap=rgb2hsv(M)Rgb2ntsc转化RGB的值为NTSC颜色空间Yiqmap=rgb2ntsc(rgbmap)YIQ=rgb2ntsc(RGB)Rgb2ycbcr转化RGB的值为YCBCR颜色空间Ycbcrmap=rgb2ycbcr(rgbmap)YCBCR=rgb2ycbcr(RGB)Ycbcr2rgb转化YCBCR的值为RGB颜色空间Rgbmap=ycbcr2rgb(ycbcrmap)RGB=ycbcr2rgb(YCBCR)N

21、tsc2rgb转化NTSC的值为RGB颜色空间Rgbmap=ntsc2rgb(yiqmap)RGB=ntsc2rgb(YIQ)表A-12边沿和块处理函数函数功能语法Bestblk确定进行块操作的块大小Siz=bestblk(mn,k)mb,nb=bestblk(m,n,k)Blkproc实现图像的显示块操作B=blkproc(A,mn,fun)B=blkproc(A,mn,fun,P1,P2,)B=blkproc(A,mn,mbordernborder,fun,)Col2im将矩阵的列重新组织到块中A=col2im(B,mn,mmnn,block_type)A=col2im(B,mn,mmnn

22、)Colfilt利用列相关函数进行边沿操作B=colfilt(b,mn,block_type,fun)B=colfilt(b,mn,block_type,fun,P1,P2,)B=colfilt(b,mn,mbordernborder,)B=colfilt(A,indexed,)Im2col重调图像块为列B=im2col(A,mn,block_type)B=im2col(A,mn)B=im2col(A,indexed,)Nlfilter进行边沿操作B=nlfilter(A,mn,fun)B=nlfilter(A,mn,fun,P1,P2,)B=nlfilter(A,indexed,)表A-13

23、区域处理函数函数功能语法Roicolor选择感兴趣的颜色区BW=roicolor(A,low,high)BW=roicolor(A,v)Roifill在图像的任意区域中进行平滑插补J=roifill(I,c,r)J=roifill(I)J=roifill(I,BW)J,BW=roifill()J=roifill(x,y,I,xi,yi)x,y,J,BW,xi,yi=roifill()Roifilt2过滤敏感区域J=roifilt2(h,I,BW)J=roifilt2(I,BW,fun)J=roifilt2(I,BW,fun,P1,P2,)Roipoly选择一个敏感的多边形区域BW=roipol

24、y(I,c,r)BW=roipoly(I)BW=roipoly(x,y,I,xi,yi)BW,xi,yi=roipoly()x,y,BW,xi,yi=roipoly()表A-14图像类型和类型转换函数函数功能语法Dither通过抖动增加外观颜色分辨率，转换图像X=dither(RGB,map)BW=dither(I)Gray2ind转换灰度图像为索引色图像X,map=gray2ind(I,n)X,map=gray2ind(BW,n)Grayslice从灰度图像创建索引图像X=grayslice(I,n)Xgrayslice(I,v)Im2bw转换图像为二进制图像BW=im2bw(I,level

25、)BW=im2bw(I,map,level)BW=im2bw(RGB,level)Im2double转换图像矩阵为双精度型I2=im2double(I1)RGB2=im2double(RGB1)I=im2double(BW)X2=im2double(X1,dindexed)Double转换数据为双精度型Double(x)Uint8转换数据为8位无符号整型I=uint8(x)Im2uint8转换图像矩阵为8位无符号整型I2=im2uint8(I1)RGB2=im2uint8(RGB1)I=im2uint8(BW)X2=im2uint8(X1,indexed)Im2uint16转换图像矩阵为16位无符号整型I2=im2uint16(I1)RGB2=im2uint16(RGB1)