高斯滤波函数(二维)my.doc

void Snake_Fun:Gauss_Image(WORD*m_Image_Data,int m_Image_Colunms,int m_Image_Rows,int m_Image_Layers,int kerner ,double sigma)int colunm=m_Image_Colunms; /输入图像数据int row=m_Image_Rows;int layer=m_Image_Layers;int plane_rc_data=row*colunm;int plane_tol_data=layer*plane_rc_data; int half_kerner=(kerner+1)/2-1; /模板步长；WORD * G_Image=new WORDplane_tol_data; /高斯滤波后的图像for (int i=0;iplane_tol_data;i+)G_Imagei=0; double *Gauss_temp=new double*kerner; /高斯矩阵for (int i=0;ikerner;i+)Gauss_tempi=new doublekerner;double *Gauss_One=new doublekerner*kerner; /一维高斯数组for (int i=0;ikerner*kerner;i+)Gauss_Onei=0;double * gau_x=new double *kerner;double * gau_y=new double *kerner;double* gau_xx=new double*kerner;double *gau_yy=new double *kerner;for (int i=0;ikerner;i+)gau_xi=new double kerner;gau_yi=new double kerner;gau_xxi=new doublekerner;gau_yyi=new double kerner;for (int i=0;ikerner;i+)int row_offset=kerner-i-1;for (int j=0;jkerner;j+)int colunm_offset=kerner-j-1;gau_xrow_offsetcolunm_offset=i-(kerner-1)/2;for (int i=0;ikerner;i+)for (int j=0;jkerner;j+)gau_yji=gau_xij;for (int i=0;ikerner;i+)for (int j=0;jkerner;j+)gau_xxij=gau_xij*gau_xij;gau_yyij=gau_yij*gau_yij;for (int i=0;ikerner;i+)for (int j=0;jkerner;j+)Gauss_tempij=exp(-(gau_xxij+gau_yyij)/(2*sigma); double max_ker=0;for (int i=0;ikerner;i+) /二维模板转化为一维数组for (int j=0;jkerner;j+)Gauss_Onei*kerner+j=Gauss_tempij;max_ker+=Gauss_Onei*kerner+j;for (int i=0;ikerner*kerner;i+)Gauss_Onei=Gauss_Onei/max_ker;Conv2D(m_Image_Data,G_Image,Gauss_One,m_Image_Colunms,m_Image_Rows,m_Image_Layers,kerner,kerner);memcpy(m_Image_Data,G_Image,plane_tol_data*sizeof(WORD);if (Gauss_temp!=NULL)for (int i=0;ikerner;i+)delete Gauss_tempi;Gauss_tempi=NULL;delete Gauss_temp;Gauss_temp=NULL;delete Gauss_One;/*二维卷积函数*/void Snake_Fun:Conv2D(WORD*m_Image_Data,WORD *Output_Image,double*Template_Filter,int m_Image_Colunms,int m_Image_Rows,int m_Image_Layers,int Template_Colunms,int Template_Rows)int i,j;int filter_center_colunm=(Template_Colunms+1)/2-1; /滤波模板偏移步长int filter_center_row=(Template_Rows+1)/2-1; int Temp_Filer_numbers=Template_Rows*Template_Colunms; /模板数据int Temp_Tol_Numbers=Temp_Filer_numbers*m_Image_Layers;double*Template_Filter_Copy=new doubleTemp_Tol_Numbers; /滤波模板的Copyfor (i=0;iTemp_Tol_Numbers;i+)Template_Filter_Copyi=0;for (i=0;iTemplate_Rows;i+) /给Copy模板赋值 int row_offset=Template_Rows-i-1; /行偏移量（R=3，,1,0）for (j=0;jTemplate_Colunms;j+) int colunm_offset=Template_Colunms-j-1; /列偏移量（R=3，,1,0） Template_Filter_Copycolunm_offset+row_offset=Template_Filteri*Template_Colunms+j; /给Copy赋值 int filter_colunm;int filter_row;int colunm_offset;int row_offset;double sum_all=0;WORD *p=Output_Image; /输出图像for (int layer=0;layerm_Image_Layers;layer+) int T_Number=layer*m_Image_Colunms*m_Image_Rows;for (int i=0;im_Image_Rows;i+) /输入图像行 for (int j=0;jm_Image_Colunms;j+) /输入图像列 sum_all=0;for (filter_row=0;filter_rowTemplate_Rows;filter_row+) /滤波模板行 row_offset=i+filter_row-filter_center_row; /图像行偏移量if (row_offsetm_Image_Rows-1) row_offset=m_Image_Rows-1; row_offset=row_offset*m_Image_Colunms; /图像的每行数据for (filter_colunm=0;filter_colunmTemplate_Colunms;filter_colunm+) colunm_offset=j+filter_colunm-filter_center_colunm; / 图像列偏移if (colunm_offsetm_Image_Colunms-1)colunm_offset=m_Image_Colunms-1;if (row_offset!=0&colunm_offset!=0)int sd=0;sum_all+=m_Image_Datarow_offset+colunm_offset+T_N