图像边缘检测—sobel算子（灰度图像，彩色图像）

╰+攻爆jí腚メ 2022-09-28 11:58 408阅读 0赞

图像为 I.然后进行如下的操作：

为了在一副图像f的（x,y）位置处寻找边缘的强度和方向，所选择的工具就是梯度，向量定义为：

![20170311124650665][]

![20170311125646118][]

![20170311125659055][]

分别在x和y两个方向求导。

![20170311130645567][]

该点梯度:

![20170311130855117][]

梯度的方向：

![20170311130921231][]

以下是灰度图与灰度图sobel边缘

![20170311131339655][]

![20170311132331674][]

vc++ MFC编写的程序，灰度图图像像素数组是静态申请的，Data\[i\]\[j\]为像素值，i,j为坐标，因为像素申请int 型，处理结果可能会超出\[0,255\]，所以结果要判断大于255为255。像素类型为unsigned char就不会出现这个问题。

void CShowPicView::OnSOBELgradient() //SOBEL梯度  //Sobel边缘检测算法
    {
    	CShowPicDoc* pDoc = GetDocument();
    	CDC* pDC=GetDC();
    	// 字符串
    	CString str;
    
    	int lWidth	=intWidth;
    	int lHeight =intHeight;
    	int			i;
    	int			j;
    	
    	unsigned char g[610][800];
    	int gx,gy,temp1;
    	for(j = 1; j < intWidth-1; j++)
    	{
    		for(i = 1; i 
       
        255)
    				g[i][j]=255;
    			else
    				g[i][j]=temp1;
    
    			pDC->SetPixel(j+intWidth+30,i,RGB(g[i][j],g[i][j],g[i][j]));
    			
    		}
    	}
    
    
    	str.Format("SOBEL");
    	pDC->TextOut((int)(intWidth*1.5+50), intHeight, str);
    	
    }

以下是原图（彩色图）与彩色图sobel边缘：

![20170311131441251][]

![20170311131432921][]

vc++ MFC编写的程序，彩色图图像像素数组是动态申请的，pic\[y\]\[x\]\[0\]，pic\[y\]\[x\]\[1\]，pic\[y\]\[x\]\[2\] 为原图的三通道的像素值，x，y为坐标值

void CShowPicView::Ontwodimension() 
    {
    	CShowPicDoc* pDoc = GetDocument();
    	CDC* pDC=GetDC();
    	// 字符串
    	CString str;
    	int x,y;
    	int i,n;
    	x=intHeight;
    	y=intWidth;
    
    	int **g1,**g2,**g3;
    
    	g1 = new int*[x]; //行 //申请行的空间
    	g2 = new int*[x]; 
    	g3 = new int*[x]; 
    	//每行的列申请空间
    	for(i=0; i
       
        pic[y+1][x-1][0]+2*pDoc->pic[y+1][x][0]+pDoc->pic[y+1][x+1][0] - pDoc->pic[y-1][x-1][0]-2*pDoc->pic[y-1][x][0]-pDoc->pic[y-1][x+1][0];
    		gy1=pDoc->pic[y-1][x-1][0]+2*pDoc->pic[y][x-1][0]+pDoc->pic[y+1][x-1][0] - pDoc->pic[y-1][x+1][0]-2*pDoc->pic[y][x+1][0]-pDoc->pic[y+1][x+1][0];
    		if(sqrt(gx1*gx1+gy1*gy1)>255)
    			g1[y][x]=255;
    		else
    			g1[y][x]=sqrt(gx1*gx1+gy1*gy1);
    
    		gx2=pDoc->pic[y+1][x-1][1]+2*pDoc->pic[y+1][x][1]+pDoc->pic[y+1][x+1][1] - pDoc->pic[y-1][x-1][1]-2*pDoc->pic[y-1][x][1]-pDoc->pic[y-1][x+1][1];
    		gy2=pDoc->pic[y-1][x-1][1]+2*pDoc->pic[y][x-1][1]+pDoc->pic[y+1][x-1][1] - pDoc->pic[y-1][x+1][1]-2*pDoc->pic[y][x+1][1]-pDoc->pic[y+1][x+1][1];
    		
    		if(sqrt(gx2*gx2+gy2*gy2)>255)
    			g2[y][x]=255;
    		else
    			g2[y][x]=sqrt(gx2*gx2+gy2*gy2);
    
    		gx3=pDoc->pic[y+1][x-1][2]+2*pDoc->pic[y+1][x][2]+pDoc->pic[y+1][x+1][2] - pDoc->pic[y-1][x-1][2]-2*pDoc->pic[y-1][x][2]-pDoc->pic[y-1][x+1][2];
    		gy3=pDoc->pic[y-1][x-1][2]+2*pDoc->pic[y][x-1][2]+pDoc->pic[y+1][x-1][2] - pDoc->pic[y-1][x+1][2]-2*pDoc->pic[y][x+1][2]-pDoc->pic[y+1][x+1][2];
    		if(sqrt(gx3*gx3+gy3*gy3)>255)
    			g3[y][x]=255;
    		else
    			g3[y][x]=sqrt(gx3*gx3+gy3*gy3);
    
    
    		pDC->SetPixel(x+1*intWidth+30,y,RGB(g1[y][x],g2[y][x],g3[y][x]));
    		}
    	}
    
    	for(i=0;i

[20170311124650665]: /images/20220708/bb0aa8a5741f4d96a2f4c9a46743b401.png
[20170311125646118]: /images/20220708/ac9e8b4197574c57b0f5992071229b28.png
[20170311125659055]: /images/20220708/355bb6d3fc9a4712812a2bb2576cf747.png
[20170311130645567]: /images/20220708/2ced1309fbf6412ca389c0c1fa89dd73.png
[20170311130855117]: /images/20220708/45075d8d4d994539afe1443a998dcca6.png
[20170311130921231]: /images/20220708/8c79ffecd598414490fee248deb7b541.png
[20170311131339655]: /images/20220708/c196c98ef2114d869fee7a3e40e6a10e.png
[20170311132331674]: /images/20220708/27a2fb75bdaa4700b2d2b1e22c2d5e25.png
[20170311131441251]: /images/20220708/323f6dfc919b45139cb198e6ff64f010.png
[20170311131432921]: /images/20220708/66bfb510831345a2ab7aafb3948ad69f.png