自适应阈值分割（vc实现）

1.以8×8邻域

划分太细，整体效果像铅笔素描。

void CISLSView::OnThresholdAdaptive88()
    {
//程序编制：李立宗
//[email protected]
//2012-8-14
        if(myImage1.IsNull())
            OnOpenResourceFile();
        if(!myImage2.IsNull())
            myImage2.Destroy();
        if(myImage2.IsNull()){
            myImage2.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
        }
                if(myImage3.IsNull()){
            myImage3.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
        }
        //COLORREF pixel;
        int maxY = myImage1.GetHeight();
        int maxX=myImage1.GetWidth();
        byte* pRealData;
        byte* pRealData2;
        byte* pRealData3;
        pRealData=(byte*)myImage1.GetBits();
        pRealData2=(byte*)myImage2.GetBits();
        pRealData3=(byte*)myImage3.GetBits();
        int pit=myImage1.GetPitch();
        int pit2=myImage2.GetPitch();
        int pit3=myImage3.GetPitch();
        //需要注意,pit和pit2的值并不一样,所以如果使用一个值,会导致不同的结果出现
        //CString str;
        //str.Format(TEXT("%d"),pit);
        //MessageBox(str);
        //str.Format(TEXT("%d"),pit2);
        //MessageBox(str);
        int bitCount=myImage1.GetBPP()/8;
        int bitCount2=myImage2.GetBPP()/8;
        int bitCount3=myImage3.GetBPP()/8;
        int tempR,tempG,tempB;
        //float temp,tempX,tempY;
        int temp;
        int T=128;
        //int pixel[4];
        float u0,u1;   //均值
        float w0,w1;   //概率
        float sum0,sum1;  //像素和
        int optIndex,optT;   //最优阈值，及其所在像素的值
        float fVaria,fMaxVaria=0;   //临时方差,最大方差
        int i;        //循环变量
        //int pixelR[256],pixelG[256],pixelB[256];
        int pixel[256]={0};   //不要忘记初始化
        //灰度化
        for (int y=0; y
            for (int x=0; x
                temp=*(pRealData+pit*(y)+(x)*bitCount);
                if(bitCount==3)
                {
                    tempR=*(pRealData+pit*(y)+(x)*bitCount);
                    tempG=*(pRealData+pit*(y)+(x)*bitCount+1);
                    tempB=*(pRealData+pit*(y)+(x)*bitCount+2);
                    temp=(int)(tempR*0.49+tempG*0.31+tempB*0.2);
                    //temp=(int)((tempR+tempG+tempB)/3);
                }
                *(pRealData3+pit3*(y)+(x)*bitCount3)=temp;
                *(pRealData3+pit3*(y)+(x)*bitCount3+1)=temp;
                *(pRealData3+pit3*(y)+(x)*bitCount3+2)=temp;

            }
        }
        //计算除边界外的点
        for (int y=1; y
            for (int x=1; x
                temp=*(pRealData3+pit3*(y)+(x)*bitCount3);
                T=*(pRealData3+pit3*(y-1)+(x-1)*bitCount3)+*(pRealData3+pit3*(y-1)+(x)*bitCount3)+*(pRealData3+pit3*(y-1)+(x+1)*bitCount3)
                +*(pRealData3+pit3*(y)+(x-1)*bitCount3)+*(pRealData3+pit3*(y)+(x)*bitCount3)+*(pRealData3+pit3*(y)+(x+1)*bitCount3)+
                *(pRealData3+pit3*(y+1)+(x-1)*bitCount3)+*(pRealData3+pit3*(y+1)+(x)*bitCount3)+*(pRealData3+pit3*(y+1)+(x+1)*bitCount3);
                T=(int)(T/9.0);
        //              CString str;
        //str.Format(TEXT("%d"),T);
        //MessageBox(str);
                if(temp>T)
                    temp=255;
                else
                temp=0;

                *(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
            }
        }
        Invalidate();
    }

void CISLSView::OnThresholdAdaptive88()
	{
//程序编制：李立宗
//[email protected]
//2012-8-14
		if(myImage1.IsNull())
			OnOpenResourceFile();
		if(!myImage2.IsNull())
			myImage2.Destroy();
		if(myImage2.IsNull()){
			myImage2.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
		}
				if(myImage3.IsNull()){
			myImage3.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
		}
		//COLORREF pixel; 
		int maxY = myImage1.GetHeight();
		int maxX=myImage1.GetWidth();
		byte* pRealData;
		byte* pRealData2;
		byte* pRealData3;
		pRealData=(byte*)myImage1.GetBits();
		pRealData2=(byte*)myImage2.GetBits();
		pRealData3=(byte*)myImage3.GetBits();
		int pit=myImage1.GetPitch();
		int pit2=myImage2.GetPitch();
		int pit3=myImage3.GetPitch();
		//需要注意,pit和pit2的值并不一样,所以如果使用一个值,会导致不同的结果出现
		//CString str;
		//str.Format(TEXT("%d"),pit);
		//MessageBox(str);
		//str.Format(TEXT("%d"),pit2);
		//MessageBox(str);
		int bitCount=myImage1.GetBPP()/8;
		int bitCount2=myImage2.GetBPP()/8;
		int bitCount3=myImage3.GetBPP()/8;
		int tempR,tempG,tempB;
		//float temp,tempX,tempY;
		int temp;
		int T=128;
		//int pixel[4];
		float u0,u1;   //均值
		float w0,w1;   //概率
		float sum0,sum1;  //像素和
		int optIndex,optT;   //最优阈值，及其所在像素的值
		float fVaria,fMaxVaria=0;   //临时方差,最大方差
		int i;        //循环变量
		//int pixelR[256],pixelG[256],pixelB[256];
		int pixel[256]={0};   //不要忘记初始化
		//灰度化
		for (int y=0; yT)
					temp=255;
				else
				temp=0;

				*(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
				*(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
				*(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
			}
		}
		Invalidate();
	}

2.将图像划分为四个区域计算

该模式缺点，可以看到四个区域之间具有明显的边界。

void CISLSView::OnThresholdAdaptive41()
    {
//程序编制：李立宗 [email protected]
//2012-8-14
        if(myImage1.IsNull())
            OnOpenResourceFile();
        if(!myImage2.IsNull())
            myImage2.Destroy();
        if(myImage2.IsNull()){
            myImage2.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
        }
                if(myImage3.IsNull()){
            myImage3.Create(myImage1.GetWidth(),myImage1.GetHeight(),24,0);
        }
        //COLORREF pixel;
        int maxY = myImage1.GetHeight();
        int maxX=myImage1.GetWidth();
        byte* pRealData;
        byte* pRealData2;
        byte* pRealData3;
        pRealData=(byte*)myImage1.GetBits();
        pRealData2=(byte*)myImage2.GetBits();
        pRealData3=(byte*)myImage3.GetBits();
        int pit=myImage1.GetPitch();
        int pit2=myImage2.GetPitch();
        int pit3=myImage3.GetPitch();
        //需要注意,pit和pit2的值并不一样,所以如果使用一个值,会导致不同的结果出现
        //CString str;
        //str.Format(TEXT("%d"),pit);
        //MessageBox(str);
        //str.Format(TEXT("%d"),pit2);
        //MessageBox(str);
        int bitCount=myImage1.GetBPP()/8;
        int bitCount2=myImage2.GetBPP()/8;
        int bitCount3=myImage3.GetBPP()/8;
        int tempR,tempG,tempB;
        //float temp,tempX,tempY;
        int temp;
        int T=128;
        //int pixel[4];
        float u0,u1;   //均值
        float w0,w1;   //概率
        float sum0,sum1;  //像素和
        int optIndex,optT;   //最优阈值，及其所在像素的值
        float fVaria,fMaxVaria=0;   //临时方差,最大方差
        int i;        //循环变量
        //int pixelR[256],pixelG[256],pixelB[256];
        int pixel[256]={0};   //不要忘记初始化
        int sum=0,avg;
        //灰度化
        for (int y=0; y
            for (int x=0; x
                temp=*(pRealData+pit*(y)+(x)*bitCount);
                if(bitCount==3)
                {
                    tempR=*(pRealData+pit*(y)+(x)*bitCount);
                    tempG=*(pRealData+pit*(y)+(x)*bitCount+1);
                    tempB=*(pRealData+pit*(y)+(x)*bitCount+2);
                    temp=(int)(tempR*0.49+tempG*0.31+tempB*0.2);
                    //temp=(int)((tempR+tempG+tempB)/3);
                }
                *(pRealData3+pit3*(y)+(x)*bitCount3)=temp;
                *(pRealData3+pit3*(y)+(x)*bitCount3+1)=temp;
                *(pRealData3+pit3*(y)+(x)*bitCount3+2)=temp;

            }
        }
        //计算左上角阈值
        for (int y=0; y
            for (int x=0; x
                sum+=*(pRealData3+pit3*(y)+(x)*bitCount3);
            }
        }
        avg=(int)(sum/(maxY/2*(maxX/2)));
        //处理左上角
        for (int y=0; y
            for (int x=0; x
                temp=*(pRealData3+pit3*(y)+(x)*bitCount3);
                if(temp>avg)
                    temp=255;
                else
                temp=0;

                *(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
            }
        }
        //右上角
        sum=0;
        for (int y=0; y
            for (int x=maxX/2; x
                sum+=*(pRealData3+pit3*(y)+(x)*bitCount3);
            }
        }
        avg=(int)(sum/(maxY/2*(maxX/2)));
        for (int y=0; y
            for (int x=maxX/2; x
                temp=*(pRealData3+pit3*(y)+(x)*bitCount3);
                if(temp>avg)
                    temp=255;
                else
                temp=0;

                *(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
            }
        }
        //左下角
        sum=0;
                for (int y=maxY/2; y
            for (int x=0; x
                sum+=*(pRealData3+pit3*(y)+(x)*bitCount3);
            }
        }
        avg=(int)(sum/(maxY/2*(maxX/2)));
        for (int y=maxY/2; y
            for (int x=0; x
                temp=*(pRealData3+pit3*(y)+(x)*bitCount3);
                if(temp>avg)
                    temp=255;
                else
                temp=0;

                *(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
            }
        }
        //右下角
        sum=0;
                for (int y=maxY/2; y
            for (int x=maxX/2; x
                sum+=*(pRealData3+pit3*(y)+(x)*bitCount3);
            }
        }
        avg=(int)(sum/(maxY/2*(maxX/2)));
        for (int y=maxY/2; y
            for (int x=maxX/2; x
                temp=*(pRealData3+pit3*(y)+(x)*bitCount3);
                if(temp>avg)
                    temp=255;
                else
                temp=0;

                *(pRealData2+pit2*(y)+(x)*bitCount2)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+1)=temp;
                *(pRealData2+pit2*(y)+(x)*bitCount2+2)=temp;
            }
        }


        Invalidate();
    }