matlab图像处理

I=imread('D:\我的文档\MATLAB\cameraman.bmp')

J0=imnoise(I,'gaussian')

J1=imnoise(I,'salt &pepper')

J0J3=imfilter(J0,fspecial('average'))

J0J5=imfilter(J0,fspecial('average',[5 5]))

J0Z3=medfilt2(J0)

J0Z5=medfilt2(J0,[5 5])

J1J3=imfilter(J1,fspecial('average'))

J1J5=imfilter(J1,fspecial('average',[5 5]))

J1Z3=medfilt2(J1)

J1Z5=medfilt2(J1,[5 5])

subplot(2,2,1),imshow(I)

title('原始图像')

subplot(2,2,2),imshow(J0)

title('加入零均值高斯噪声')

subplot(2,2,3),imshow(J1)

title('加入椒盐噪声')

figure,

subplot(2,2,1),imshow(J0J3)

title('对高斯噪声，采用3x3均值滤波')

subplot(2,2,2),imshow(J0J5)

title('对高斯噪声，采用5x5均值滤波')

subplot(2,2,3),imshow(J0Z3)

title('对高斯噪声，采用3x3中值滤波')

subplot(2,2,4),imshow(J0Z5)

title('对高斯噪声，宽拆采用5x5中慎纳枣值滤波')

figure,

subplot(2,2,1),imshow(J1J3)

title('对椒盐噪声，采用3x3均值茄败滤波')

subplot(2,2,2),imshow(J1J5)

title('对椒盐噪声，采用5x5均值滤波')

subplot(2,2,3),imshow(J1Z3)

title('对椒盐噪声，采用3x3中值滤波')

subplot(2,2,4),imshow(J1Z5)

title('对椒盐噪声，采用5x5中值滤波')

%之前写的一个程序，这里面用Sobel算子和Prewitt算子的部分就是对图像锐化得到边缘的了。也可以直接用matlab自带的函数S = edge(I, 'sobel')进行锐化。

clc

close all

clear all

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%读入图像

f=imread('Pictures/4_m03.tif')

%f=imread('Pictures/5_m01.tif')

%f=imread('Pictures/10_m02.tif')

%f=imread('Pictures/22_m03.tif')

f=imresize(f,0.25)

f=im2double(f)

[m,n]=size(f)

subplot(2,3,1),imshow(f)

title('原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%生成高斯平滑滤波模板

hg=zeros(3,3)  %设定模板大小3*3

delta=0.5

for x=1:1:3

    for y=1:1:3

        u=x-2

        v=y-2

   谨带     hg(x,y)=exp(-(u^2+v^2)/(2*pi*delta^2))

    end

end

h=hg/sum(hg(:))

%高斯滤波

ftemp=zeros(m,n)

rowhigh=m-1

colhigh=n-1

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

    竖迹    A=h.*mod

        ftemp(x,y)=sum(A(:))

    end

end

f=ftemp

subplot(2,3,4),imshow(f)

title('高斯滤波后的图像')

 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%利用Sobel算子进行边缘检测

sx=[-1 0 1-2 0 2-1 0 1]

sy=[-1 -2 -10 0 01 2 1]

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) 祥纤芦f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

        fsx=sx.*mod

        fsy=sy.*mod

        ftemp(x,y)=max((abs(sum(fsx(:)))),(abs(sum(fsy(:)))))

    end

end

fs=im2uint8(ftemp)

subplot(2,3,2),imshow(fs)

title('Sobel算子进行边缘检测的原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%阈值分割

TH1=140  %设定阈值

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        if (fs(x,y)>=TH1)&((fs(x,y-1) <= fs(x,y)) & (fs(x,y) > fs(x,y+1)) )

          fs(x,y)=200

      elseif(fs(x,y)>=TH1)&( (fs(x-1,y) <=fs(x,y)) & (fs(x,y) >fs(x+1,y)))

          fs(x,y)=200

      else fs(x,y)=50

        end

    end

end

subplot(2,3,5),imshow(fs)

title('Sobel算子边缘检测并细化后的图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%利用Prewitt算子进行边缘检测

sx=[1 0 -11 0 -11 0 -1]

sy=[-1 -1 -10 0 01 1 1]

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        mod=[f(x-1,y-1) f(x-1,y) f(x-1,y+1) f(x,y-1) f(x,y) f(x,y+1)f(x+1,y-1) f(x+1,y) f(x+1,y+1)]

        fsx=sx.*mod

        fsy=sy.*mod

        ftemp(x,y)=max((abs(sum(fsx(:)))),(abs(sum(fsy(:)))))

    end

end

fs=im2uint8(ftemp)

subplot(2,3,3),imshow(fs)

title('Prewitt算子进行边缘检测的原始图像')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%阈值分割

TH1=100  %设定阈值

for x=2:1:rowhigh-1

    for y=2:1:colhigh-1

        if (fs(x,y)>=TH1)&((fs(x,y-1) <= fs(x,y)) & (fs(x,y) > fs(x,y+1)) )

          fs(x,y)=200

      elseif(fs(x,y)>=TH1)&( (fs(x-1,y) <=fs(x,y)) & (fs(x,y) >fs(x+1,y)))

          fs(x,y)=200

      else fs(x,y)=50

        end

    end

end

subplot(2,3,6),imshow(fs)

title('Prewitt算子边缘检测并细化后的图像')

clc,clear

a

=

1:1:6

%横坐标

b

=

[8.0

9.0

10.0

15.0

35.0

40.0]

%纵坐标

plot(a,

b,

'b')

%自物漏然状态的画图效果

hold

on

%第一种带举，画平滑曲蠢蚂碧线的方法

c

=

polyfit(a,

b,

2)

%进行拟合，c为2次拟合后的系数

d

=

polyval(c,

a,

1)

%拟合后，每一个横坐标对应的值即为d

plot(a,

d,

'r')

%拟合后的曲线

plot(a,

b,

'*')

%将每个点

用*画出来

hold

on

%第二种，画平滑曲线的方法

values

=

spcrv([[a(1)

a

a(end)][b(1)

b

b(end)]],3)

plot(values(1,:),values(2,:),

'g')

建议学会使用搜索引擎，百度“matlab曲线平滑“出来一堆方法

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