C++实现基础图像处理

最近在做项目，开始接触数字图像处理方面的东西。一时兴起，结合数字图像处理的基本知识和opencv的基本了解，写了一个数字图像处理基本类。类里实现的功能见代码。

 

环境：vs2008 + opencv

 

头文件EDIP.h (Enjoy's Digital Image Processing)

////////////////////////////////////////////功能：对数字图像进行空间域、频域的处理//作者：IR小组成员//时间：2010年01月16日//版本：alpha 1.0.0//////////////////////////////////////////#include "cxcore.h"class EDIP{private:public:EDIP();virtual ~EDIP();//Sobel算子//原始图像src 处理后的图像dst 处理方向drt （1、x方向； 2、y方向）void sobel(const IplImage * src, IplImage * dst, int drt);//Laplace算子//原始图像src 处理后的图像dst 掩模方式mode_handle （1、标准模式； 2、对角加强模式）void laplace(const IplImage * src, IplImage * dst, int mode_handle);//负片//原始图像src 处理后的图像dstvoid negative_file(const IplImage * src, IplImage * dst);//标定//原始图像src 处理后的图像dstvoid calibration(long ** t_1, long ** t_2, long ** t_3, int nrow, int ncol);};

 

EDIP.cpp

////////////////////////////////////////////功能：对数字图像进行空间域、频域的处理//作者：IR小组成员//时间：2010年01月16日//版本：alpha 1.0.0//////////////////////////////////////////#include "stdafx.h"#include "edip.h"EDIP::EDIP(){}EDIP::~EDIP(){}void EDIP::sobel(const IplImage *src, IplImage *dst, int drt){long sob[3][3] = {0}; //Sobel算子掩模long ** atemp_1; //临时容器1long ** atemp_2; //临时容器2long ** atemp_3; //临时容器3int h = src->height; //原始图像高度或行数int w = src->width; //原始图像宽度或列数//加强x方向边缘的Sobel算子掩模if (drt == 1){sob[0][0] = -1; sob[0][1] = -2; sob[0][2] = -1;sob[1][0] = 0; sob[1][1] = 0; sob[1][2] = 0;sob[2][0] = 1; sob[2][1] = 2; sob[2][2] = 1;}//加强y方向边缘的Sobel算子掩模else if (drt == 2){sob[0][0] = -1; sob[0][1] = 0; sob[0][2] = 1;sob[1][0] = -2; sob[1][1] = 0; sob[1][2] = 2;sob[2][0] = -1; sob[2][1] = 0; sob[2][2] = 1;}//为临时容器1申请空间，存放原始图片第一个通道的处理结果atemp_1 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_1[i] = (long *) malloc (w * sizeof(long));//为临时容器2申请空间，存放原始图片第二个通道的处理结果atemp_2 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_2[i] = (long *) malloc (w * sizeof(long));//为临时容器3申请空间，存放原始图片第三个通道的处理结果atemp_3 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_3[i] = (long *) malloc (w * sizeof(long));//对原始图像进行Sobel加强for (int row = 0; row < h; row++){if (row == 0 || row == 1 || row == h-2 || row == h-1) continue;for (int col = 0; col < w; col++){if (col == 0 || col == 1 || col == w-2 || col == w-1) continue;long temp_1 = 0;long temp_2 = 0;long temp_3 = 0;for (int i = -1; i < 2; i++){uchar * ptr_s = (uchar *)(src->imageData + (row + i) * src->widthStep);for (int j = -1; j< 2; j++){temp_1 += ptr_s[3 * (col + j)] * sob[i + 1][j + 1];temp_2 += ptr_s[3 * (col + j) + 1] * sob[i + 1][j + 1];temp_3 += ptr_s[3 * (col + j) + 2] * sob[i + 1][j + 1];}}atemp_1[row][col] = temp_1;atemp_2[row][col] = temp_2;atemp_3[row][col] = temp_3;}}//对临时容器中的处理结果进行标定，使其中值介于[0,255]之间calibration(atemp_1, atemp_2, atemp_3, h, w);//将标定后的结果赋给目标变量for (int row = 0; row < h; row++){uchar * ptr_d = (uchar *)(dst->imageData + row * dst->widthStep);for (int col = 0; col < w; col++){ptr_d[3 * col] = (uchar)(atemp_1[row][col]);ptr_d[3 * col + 1] = (uchar)(atemp_2[row][col]);ptr_d[3 * col + 2] = (uchar)(atemp_3[row][col]);}}//释放临时容器free(atemp_1);free(atemp_2);free(atemp_3);}void EDIP::laplace(const IplImage *src, IplImage *dst, int mode_handle){long lap[3][3] = {0}; //Laplace算子3*3掩模long ** atemp_1; //临时容器1long ** atemp_2; //临时容器2long ** atemp_3; //临时容器3int h = src->height; //原始图像高度或行数int w = src->width; //原始图像宽度或列数//标准Laplace算子掩模if (mode_handle == 1){lap[0][0] = 0; lap[0][1] = 1; lap[0][2] = 0;lap[1][0] = 1; lap[1][1] = -4; lap[1][2] = 1;lap[2][0] = 0; lap[2][1] = 1; lap[2][2] = 0;}//兼顾对角方向的Laplace算子掩模else if (mode_handle == 2){lap[0][0] = 1; lap[0][1] = 1; lap[0][2] = 1;lap[1][0] = 1; lap[1][1] = -8; lap[1][2] = 1;lap[2][0] = 1; lap[2][1] = 1; lap[2][2] = 1;}//为临时容器1申请空间，存放原始图片第一个通道的处理结果atemp_1 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_1[i] = (long *) malloc (w * sizeof(long));//为临时容器2申请空间，存放原始图片第二个通道的处理结果atemp_2 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_2[i] = (long *) malloc (w * sizeof(long));//为临时容器3申请空间，存放原始图片第三个通道的处理结果atemp_3 = (long **) malloc (h * sizeof(long *));for (int i = 0; i< h; i++)atemp_3[i] = (long *) malloc (w * sizeof(long));//对原始图像进行Laplace加强for (int row = 0; row < h; row++){if (row == 0 || row == 1 || row == h-2 || row == h-1) continue;for (int col = 0; col < w; col++){if (col == 0 || col == 1 || col == w-2 || col == w-1) continue;long temp_1 = 0;long temp_2 = 0;long temp_3 = 0;for (int i = -1; i < 2; i++){uchar * ptr_s = (uchar *)(src->imageData + (row + i) * src->widthStep);for (int j = -1; j< 2; j++){temp_1 += ptr_s[3 * (col + j)] * lap[i + 1][j + 1];temp_2 += ptr_s[3 * (col + j) + 1] * lap[i + 1][j + 1];temp_3 += ptr_s[3 * (col + j) + 2] * lap[i + 1][j + 1];}}atemp_1[row][col] = temp_1;atemp_2[row][col] = temp_2;atemp_3[row][col] = temp_3;}}//对临时容器中的处理结果进行标定，使其中值介于[0,255]之间calibration(atemp_1, atemp_2, atemp_3, h ,w);//将标定后的结果赋给目标变量for (int row = 0; row < h; row++){uchar * ptr_d = (uchar *)(dst->imageData + row * dst->widthStep);for (int col = 0; col < w; col++){ptr_d[3 * col] = (uchar)(atemp_1[row][col]);ptr_d[3 * col + 1] = (uchar)(atemp_2[row][col]);ptr_d[3 * col + 2] = (uchar)(atemp_3[row][col]);}}//释放临时容器free(atemp_1);free(atemp_2);free(atemp_3);}void EDIP::negative_file(const IplImage *src, IplImage *dst){int h = src->height; //原始图像高度或行数int w = src->width; //原始图像宽度或列数//对原始图像进行负片加强for (int row = 0; row < h; row++){uchar * ptr_s = (uchar *)(src->imageData + row * src->widthStep);uchar * ptr_d = (uchar *)(dst->imageData + row * dst->widthStep);for (int col = 0; col < w; col++){ptr_d[3 * col] = 255 - ptr_s[3 * col];ptr_d[3 * col + 1] = 255 - ptr_s[3 * col + 1];ptr_d[3 * col + 2] = 255 - ptr_s[3 * col + 2];}}}void EDIP::calibration(long **t_1, long **t_2, long **t_3, int nrow, int ncol){long tmax_1 = -1024; //一通道最大值long tmax_2 = -1024; //二通道最大值long tmax_3 = -1024; //三通道最大值long tmin_1 = 1024; //一通道最小值long tmin_2 = 1024; //二通道最小值long tmin_3 = 1024; //三通道最小值//找到各个通道的最小值for (int row = 0; row < nrow; row++){for (int col = 0; col < ncol; col++){if (t_1[row][col] < tmin_1) tmin_1 = t_1[row][col];if (t_1[row][col] < tmin_2) tmin_1 = t_2[row][col];if (t_1[row][col] < tmin_3) tmin_1 = t_3[row][col];}}tmin_1 = abs(tmin_1);tmin_2 = abs(tmin_2);tmin_3 = abs(tmin_3);//各通道的值加上取绝对值后的最小值，将各个通道的最小值标定为0//找到一次标定后各个通道的最大值for (int row = 0; row < nrow; row++){for (int col = 0; col < ncol; col++){t_1[row][col] = t_1[row][col] + tmin_1;if (t_1[row][col] > tmax_1) tmax_1 = t_1[row][col];t_2[row][col] = t_2[row][col] + tmin_2;if (t_2[row][col] > tmax_2) tmax_2 = t_2[row][col];t_3[row][col] = t_3[row][col] + tmin_3;if (t_3[row][col] > tmax_3) tmax_3 = t_3[row][col];}}//将各个通道的最大值表定位255for (int row = 0; row < nrow; row++){for (int col = 0; col < ncol; col++){t_1[row][col] = (long)(t_1[row][col] * 255 / tmax_1);t_2[row][col] = (long)(t_2[row][col] * 255 / tmax_2);t_3[row][col] = (long)(t_3[row][col] * 255 / tmax_3);}}}

 

 

不知道是我理解的有问题还是怎么，Laplace强化处理后，重新标定的结果基色偏黄。

其他功能有待添加