西安交通大学大学数字图像处理大作业

1、数字图像处理目录作业一1一 作业要求1二 源代码1三 运行结果3作业二5一 作业要求5二 算法描述5三 源代码7四 运行结果10作业一一 作业要求在图像的空间域滤波操作中，会出现有部分掩膜矩阵在图像外面的情况，所以需要给图像先加入一个边界，执行完操作之后，再去掉这个边界，保证图像中所有的像素都参与矩阵运算。二 源代码byte, filter(byte,f,float,mask) int w = f.GetLength(0); int h = f.GetLength(1); byte, g = new bytew,h; int M = mask.GetLength(0)/2; int N = m

2、ask.GetLength(1)/2; for (int y=N;y<h-N;y+) for (int x=M;x<w-M;x+) float s = 0; for (int m=-M;m<=M;m+) for (int n=-N;n<=N;n+) s+=fx+m,y+n*maskM+m,N+n; gx,y = SByte(s); return g;byte SByte(double v) if (v>255) return 255; if (v<0) return 0; return (byte)v; float, averagingMask(int M,

3、int N) float, mask = new float2*M+1,2*N+1; for (int m=-M;m<=M;m+) for (int n=-N;n<=N;n+) maskM+m,N+n = 1.0f/(2*M+1)*(2*N+1); return mask;byte, addboard(byte, f,int M,int N)int w=f.GetLength(0);int h=f.GetLength(1);int gw=w+2*M;int gh=h+2*N;byte, g=new bytegw,gh;/add top board and bottom boardf

4、or(int i=0;i<N;i+)for(int j=0;j<w;j+)gM+j,i=fj,0;for(int i=0;i<N;i+)for(int j=0;j<w;j+)gM+j,i+h+N=fj,h-1;/copy the imagefor(int i=0;i<w;i+)for (int j=0;j<h;j+)gi+M,j+N=fi,j;/add left and right boardfor(int i=0;i<M;i+)for (int j=0;j<gh;j+)gi,j=gM,j;for(int i=0;i<M;i+)for (i

5、nt j=0;j<gh;j+)gw+M+i,j=ggw-1-M,j;return g;byte, removeboard(byte,f,int M,int N)int w=f.GetLength(0);int h=f.GetLength(1);int gw=w-2*M;int gh=h-2*N;byte, g=new bytegw,gh;for(int i=0;i<gw;i+)for(int j=0;j<gh;j+)gi,j=fi+M,j+N;return g;void main()byte, f = LoadImg();ShowImg("f",f);in

6、t w=f.GetLength(0);int h=f.GetLength(1);int M=10,N=20;int gw=w-2*M;int gh=h-2*N;byte, boardimage=new bytegw,gh;byte, filterimage=new bytegw,gh;boardimage=addboard(f,M,N);ShowImg("boardimage",boardimage);filterimage=filter(boardimage,averagingMask(M,N);ShowImg("result",removeboard

7、(filterimage,M,N);三 运行结果原图像：加边界之后的图像：均值滤波并且去除边界的图像：作业二一 作业要求给定图像与处理结果，如图一所示，思考算法并编程实现。图一 左边为原图，右边为处理结果二 算法描述Compare the result and the original image, we can see that the program change the contrast of image and enhance the edge of Lena. Consider using intensity transform and Sobel edge detection to

8、 achieve the goal. After many experiments, I choose following intensity transform function.The graph of this function is Fig 1.Fig 1 Graph of intensity transform function Use Sobel to detect the edge of the original image.Sobel in x direction can be written as the following transform matrix:SobleX=

9、Similar, Sobel in y direction can be written as the following transform matrix:SobleY= We can use SobelX and SobelY to compute the gradient image. is the value of pixels in the gradient image, is the value of pixels in image processed by SobelX, and is the value of pixels in image processed by Sobel

10、Y. In order to decrease noise, I use the following function to process gradient image:After processing, I use 0 to replace these negative values.Because the gradient image has a very high contrast, so I use intensity transform again. After that, the final result can be calculated: All the function i

11、s chosen through experiment, maybe the result isnt the same with the teachers result, but its very similar.三 源代码byte, filter(byte,f,float,mask) int w = f.GetLength(0); int h = f.GetLength(1); int M = mask.GetLength(0)/2; int N = mask.GetLength(1)/2; byte, g = new bytew,h; for (int y=N;y<h-N;y+) f

12、or (int x=M;x<w-M;x+) float r = 0;for (int m=-M;m<=M;m+)for (int n=-N;n<=N;n+) r+=fx+m,y+n*maskM+m,N+n;gx,y=S(r); return g; byte, SobelX(byte,f) float, mask = new float3,3; mask0,0=-1; mask1,0 = 0; mask2,0 = 1; mask0,1=-2; mask1,1 = 0; mask2,1 = 2; mask0,2=-1; mask1,2 = 0; mask2,2 = 1; retu

13、rn filter(f,mask);byte, SobelY(byte,f) float, mask = new float3,3; mask0,0=-1; mask1,0 = -2; mask2,0 =-1; mask0,1= 0; mask1,1 = 0; mask2,1 = 0; mask0,2= 1; mask1,2 = 2; mask2,2 = 1; return filter(f,mask);byte S(double f) if(f>255) return 255; if(f<0) return 0; return (byte)f;byte, Scale(byte,f

14、,double a)int w = f.GetLength(0); int h = f.GetLength(1);for(int i=0;i<w;i+)for(int j=0;j<h;j+)fi,j=(byte)(fi,j*a);return f;byte, Subnum(byte,f,int a)int w = f.GetLength(0); int h = f.GetLength(1);for(int i=0;i<w;i+)for(int j=0;j<h;j+)fi,j=S(fi,j-a);return f;byte, Sub(byte,f,byte,g) int

15、w = f.GetLength(0); int h = f.GetLength(1); byte, p = new bytew,h; for(int x=0;x<w;x+) for(int y=0;y<h;y+) px,y=S(fx,y-gx,y); return p; byte, Mix(byte,fx,byte,fy) int w = fx.GetLength(0); int h = fx.GetLength(1); byte, g = new bytew,h; for (int y=0;y<h;y+) for (int x=0;x<w;x+) float px =

16、(fxx,y); float py =(fyx,y); gx,y = S(Sqrt(px*px+py*py); return g; byte, IntensityTransform(byte,f) int w = f.GetLength(0); int h = f.GetLength(1); byte, g = new bytew,h; for(int i=0;i<w;i+) for(int j=0;j<h;j+) gi,j = S(0.25*fi,j+110); return g;void main() byte , I = LoadImg(); ShowImg("Original",I); byte , I1 = IntensityTransform(I); ShowImg("IntensityTransform",I1); byte , I2 = SobelX(I); byte , I3 = SobelY(I); byte , I4 = Mix(I2,I3); ShowImg("Gradient"