西安交通大學(xué)大學(xué)數(shù)字圖像處理大作業(yè)

1、數(shù)字圖像處理目錄作業(yè)一1一 作業(yè)要求1二 源代碼1三 運(yùn)行結(jié)果3作業(yè)二5一 作業(yè)要求5二 算法描述5三 源代碼7四 運(yùn)行結(jié)果10作業(yè)一一 作業(yè)要求在圖像的空間域?yàn)V波操作中，會(huì)出現(xiàn)有部分掩膜矩陣在圖像外面的情況，所以需要給圖像先加入一個(gè)邊界，執(zhí)行完操作之后，再去掉這個(gè)邊界，保證圖像中所有的像素都參與矩陣運(yùn)算。二 源代碼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 運(yùn)行結(jié)果原圖像：加邊界之后的圖像：均值濾波并且去除邊界的圖像：作業(yè)二一 作業(yè)要求給定圖像與處理結(jié)果，如圖一所示，思考算法并編程實(shí)現(xiàn)。圖一 左邊為原圖，右邊為處理結(jié)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 源代碼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"