#include?“stdafx.h“
#include?“afx.h“
#include?“math.h“
#include?“canny.h“

//?一維高斯分布函數(shù)，用于生成平滑函數(shù)中的高斯濾波系數(shù)
void?CreatGauss（double?sigmadouble?**pdKernelint?*pnWidowSize）
{
	LONG?i;
????int?nCenter;//數(shù)組中心點(diǎn)
????double?dDis;//數(shù)組中一點(diǎn)到中心點(diǎn)距離

????double?dValue;//中間變量
????double?dSum;
????dSum?=?0;

????*pnWidowSize?=?1+?2*ceil（3*sigma）;//?[-3*sigma3*sigma]?以?xún)?nèi)數(shù)據(jù)，會(huì)覆蓋絕大部分濾波系數(shù)
????nCenter?=?（*pnWidowSize）/2;
????*pdKernel?=?new?double[*pnWidowSize];

????for（i=0;i<（*pnWidowSize）;i++）{//生成高斯數(shù)據(jù)
		dDis?=?double（i?-?nCenter）;
????????dValue?=?exp（-（1/2）*dDis*dDis/（sigma*sigma））;
????????（*pdKernel）[i]?=?dValue;
????????dSum+=dValue;
	}

????for（i=0;i<（*pnWidowSize）;i++）{//歸一化
		（*pdKernel）[i]/=dSum;
	}
}

//用高斯濾波器平滑原圖像
void?GaussianSmooth（int?wint?nHeightLPBYTE?pGrayLPBYTE?pResultdouble?sigma）
{
	LONG?x?y;
	LONG?i;
????int?nWindowSize;//高斯濾波器長(zhǎng)度
????int?nLen;//窗口長(zhǎng)度
????double?*pdKernel;//一維高斯濾波器
????double?dDotMul;//高斯系數(shù)與圖像數(shù)據(jù)的點(diǎn)乘
????double?dWeightSum;//濾波系數(shù)總和

????double?*pdTemp;
????pdTemp?=?new?double[w*nHeight];

????CreatGauss（sigma?&pdKernel?&nWindowSize）;//產(chǎn)生一維高斯數(shù)據(jù)
????nLen?=?nWindowSize/2;

????for（y=0;y		for（x=0;x			dDotMul?=?0;
????????????dWeightSum?=?0;
????????????for（i=（-nLen）;i<=nLen;i++）{
				if（（i+x）>=0?&&?（i+x）					dDotMul+=（double）pGray[y*w+（i+x）]?*?pdKernel[nLen+i];
????????????????????dWeightSum?+=?pdKernel[nLen+i];
				}
			}
????????????pdTemp[y*w+x]?=?dDotMul/dWeightSum;
		}
	}

????for（x=0;?x		for（y=0;?y			dDotMul?=?0;
????????????dWeightSum?=?0;
????????????for（i=（-nLen）;i<=nLen;i++）{
				if（（i+y）>=0?&&?（i+y）					dDotMul?+=?（double）pdTemp[（y+i）*w+x]*pdKernel[nLen+i];
????????????????????dWeightSum?+=?pdKernel[nLen+i];
				}
			}
			pResult[y*w+x]?=?（unsigned?char）dDotMul/dWeightSum;
		}
	}

????delete?[]pdKernel;
????pdKernel?=?NULL;
????delete?[]pdTemp;
????pdTemp?=?NULL;
}

//?方向?qū)?shù)求梯度
void?Grad（int?wint?nHeightLPBYTE?pGrayint?*pGradXint?*pGradYint?*pMag）
{
	LONG?yx;


????for（y=1;y		for（x=1;x			pGradX[y*w?+x]?=?（int）（?pGray[y*w+x+1]-pGray[y*w+?x-1]?）;

????for（x=1;x		for（y=1;y			pGradY[y*w?+x]?=?（int）（pGray[（y+1）*w?+x]?-?pGray[（y-1）*w?+x]）;

????//求梯度
????double?dSqt1;
????double?dSqt2;

????for（y=0;?y		for（x=0;?x			dSqt1?=?pGradX[y*w?+?x]*pGradX[y*w?+?x];//二階范數(shù)求梯度
????????????dSqt2?=?pGradY[y*w?+?x]*pGradY[y*w?+?x];
????????????pMag[y*w+x]?=?（int）（sqrt（dSqt1+dSqt2）+0.5）;
		}
}

//非最大抑制
void?NonmaxSuppress（int?*pMagint?*pGradXint?*pGradYint?wint?nHeightLPBYTE?pNSRst）
{
	LONG?yx;
????int?nPos;

????int?gx;//梯度分量
????int?gy;

????int?g1g2g3g4;//中間變量
????double?weight;
????double?dTmpdTmp1dTmp2;

????for（x=0;x		pNSRst[x]?=?0;
????????pNSRst[（nHeight-1）*w+x]?=?0;
	}
????for（y=0;y