最好的网站建设团队网站开发技术 北京
文章选自：
一、像素访问
一张图片由许多个点组成，每个点就是一个像素，每个像素包含不同的值，对图像像素操作是图像处理过程中常使用的
二、访问像素
void Samples::AccessPixels1(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------data[i] = data[i] / div * div + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//-----------------------------------【方法二】-------------------------------------------------
// 说明：利用 .ptr 和 * ++
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels2(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------*data++ = *data / div * div + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//-----------------------------------------【方法三】-------------------------------------------
// 说明：利用.ptr 和 * ++ 以及模操作
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels3(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------int v = *data;*data++ = v - v % div + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//----------------------------------------【方法四】---------------------------------------------
// 说明：利用.ptr 和 * ++ 以及位操作
//----------------------------------------------------------------------------------------------------
void Samples::AccessPixels4(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 对于 div=16, mask= 0xF0for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//------------开始处理每个像素-------------------*data++ = *data & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//----------------------------------------【方法五】----------------------------------------------
// 说明：利用指针算术运算
//---------------------------------------------------------------------------------------------------
void Samples::AccessPixels5(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));int step = image.step; //有效宽度//掩码值uchar mask = 0xFF << n; // e.g. 对于 div=16, mask= 0xF0//获取指向图像缓冲区的指针uchar *data = image.data;for (int j = 0; j < nl; j++) {for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------*(data + i) = *data & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束data += step; // next line}
}//---------------------------------------【方法六】----------------------------------------------
// 说明：利用 .ptr 和 * ++以及位运算、image.cols * image.channels()
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels6(Mat &image, int div = 64) {int nl = image.rows; //行数int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 例如div=16, mask= 0xF0for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < image.cols * image.channels(); i++) {//-------------开始处理每个像素-------------------*data++ = *data & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}// -------------------------------------【方法七】----------------------------------------------
// 说明：利用.ptr 和 * ++ 以及位运算(continuous)
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels7(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols * image.channels(); //每行元素的总元素数量if (image.isContinuous()) {//无填充像素nc = nc * nl;nl = 1; // 为一维数列}int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 比如div=16, mask= 0xF0for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------*data++ = *data & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//------------------------------------【方法八】------------------------------------------------
// 说明：利用 .ptr 和 * ++ 以及位运算 (continuous+channels)
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels8(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols; //列数if (image.isContinuous()) {//无填充像素nc = nc * nl;nl = 1; // 为一维数组}int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 比如div=16, mask= 0xF0for (int j = 0; j < nl; j++) {uchar *data = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------*data++ = *data & mask + div / 2;*data++ = *data & mask + div / 2;*data++ = *data & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}// -----------------------------------【方法九】 ------------------------------------------------
// 说明：利用Mat_ iterator
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels9(Mat &image, int div = 64) {//获取迭代器Mat_<Vec3b>::iterator it = image.begin<Vec3b>();Mat_<Vec3b>::iterator itend = image.end<Vec3b>();for (; it != itend; ++it) {//-------------开始处理每个像素-------------------(*it)[0] = (*it)[0] / div * div + div / 2;(*it)[1] = (*it)[1] / div * div + div / 2;(*it)[2] = (*it)[2] / div * div + div / 2;//-------------结束像素处理------------------------} //单行处理结束
}//-------------------------------------【方法十】-----------------------------------------------
// 说明：利用Mat_ iterator以及位运算
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels10(Mat &image, int div = 64) {// div必须是2的幂int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 比如 div=16, mask= 0xF0// 获取迭代器Mat_<Vec3b>::iterator it = image.begin<Vec3b>();Mat_<Vec3b>::iterator itend = image.end<Vec3b>();//扫描所有元素for (; it != itend; ++it) {//-------------开始处理每个像素-------------------(*it)[0] = (*it)[0] & mask + div / 2;(*it)[1] = (*it)[1] & mask + div / 2;(*it)[2] = (*it)[2] & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束
}//------------------------------------【方法十一】---------------------------------------------
// 说明：利用Mat Iterator_
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels11(Mat &image, int div = 64) {//获取迭代器Mat_<Vec3b> cimage = image;Mat_<Vec3b>::iterator it = cimage.begin();Mat_<Vec3b>::iterator itend = cimage.end();for (; it != itend; it++) {//-------------开始处理每个像素-------------------(*it)[0] = (*it)[0] / div * div + div / 2;(*it)[1] = (*it)[1] / div * div + div / 2;(*it)[2] = (*it)[2] / div * div + div / 2;//-------------结束像素处理------------------------}
}void Samples::AccessPixels12(Mat &image, int div = 64) {int nl = image.rows; //行数int nc = image.cols; //列数for (int j = 0; j < nl; j++) {for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------image.at<Vec3b>(j, i)[0] = image.at<Vec3b>(j, i)[0] / div * div + div / 2;image.at<Vec3b>(j, i)[1] = image.at<Vec3b>(j, i)[1] / div * div + div / 2;image.at<Vec3b>(j, i)[2] = image.at<Vec3b>(j, i)[2] / div * div + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//----------------------------------【方法十三】-----------------------------------------------
// 说明：利用图像的输入与输出
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels13(const Mat &image, //输入图像Mat & result, // 输出图像int div = 64) {int nl = image.rows; //行数int nc = image.cols; //列数//准备好初始化后的Mat给输出图像result.create(image.rows, image.cols, image.type());//创建无像素填充的图像nc = nc * nl;nl = 1; //单维数组int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g.比如div=16, mask= 0xF0for (int j = 0; j < nl; j++) {uchar * data = result.ptr<uchar>(j);const uchar *idata = image.ptr<uchar>(j);for (int i = 0; i < nc; i++) {//-------------开始处理每个像素-------------------*data++ = (*idata++) & mask + div / 2;*data++ = (*idata++) & mask + div / 2;*data++ = (*idata++) & mask + div / 2;//-------------结束像素处理------------------------} //单行处理结束}
}//--------------------------------------【方法十四】-------------------------------------------
// 说明：利用操作符重载
//-------------------------------------------------------------------------------------------------
void Samples::AccessPixels14(Mat &image, int div = 64) {int n = static_cast<int>(log(static_cast<double>(div)) / log(2.0));//掩码值uchar mask = 0xFF << n; // e.g. 比如div=16, mask= 0xF0//进行色彩还原image = (image & Scalar(mask, mask, mask)) + Scalar(div / 2, div / 2, div / 2);
}