本文整理汇总了C++中Histogram1D::applyLookUp方法的典型用法代码示例。如果您正苦于以下问题：C++ Histogram1D::applyLookUp方法的具体用法？C++ Histogram1D::applyLookUp怎么用？C++ Histogram1D::applyLookUp使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Histogram1D的用法示例。
在下文中一共展示了Histogram1D::applyLookUp方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: dim
//-------------------- tranforms the image to negative---------------------------------------
//-------------------- shows it's histogram values on graphic--------------------------------
void MainWindow::on_pushButton_4_clicked()
{
Histogram1D negative;
//build look up
int dim(256);
cv::Mat lut(1, &dim, CV_8U); // lut is a matrix which is in 1D
for(int i=0; i<256; i++)
{
lut.at<uchar>(i)=255-i; //takes all the values and reverses it
}
cv::Mat negativeResult;
negativeResult=negative.applyLookUp(image,lut);
cv::namedWindow("negative");
cv::imshow("negative",negativeResult);
//negative image histogram
cv::imshow("negative histogram",negative.getHistogramImage(negativeResult));
}示例2: main
int main()
{
// Read input image
cv::Mat image= cv::imread("group.jpg",0);
if (!image.data)
return 0;
// Resize by 70% for book printing
cv::resize(image, image, cv::Size(), 0.7, 0.7);
// save grayscale image
cv::imwrite("groupBW.jpg", image);
// Display the image
cv::namedWindow("Image");
cv::imshow("Image",image);
// The histogram object
Histogram1D h;
// Compute the histogram
cv::Mat histo= h.getHistogram(image);
// Loop over each bin
for (int i=0; i<256; i++)
cout << "Value " << i << " = " << histo.at<float>(i) << endl;
// Display a histogram as an image
cv::namedWindow("Histogram");
cv::imshow("Histogram",h.getHistogramImage(image));
// creating a binary image by thresholding at the valley
cv::Mat thresholded; // output binary image
cv::threshold(image,thresholded,
60, // threshold value
255, // value assigned to pixels over threshold value
cv::THRESH_BINARY); // thresholding type
// Display the thresholded image
cv::namedWindow("Binary Image");
cv::imshow("Binary Image",thresholded);
thresholded = 255 - thresholded;
cv::imwrite("binary.bmp",thresholded);
// Equalize the image
cv::Mat eq= h.equalize(image);
// Show the result
cv::namedWindow("Equalized Image");
cv::imshow("Equalized Image",eq);
// Show the new histogram
cv::namedWindow("Equalized Histogram");
cv::imshow("Equalized Histogram",h.getHistogramImage(eq));
// Stretch the image, setting the 1% of pixels at black and 1% at white
cv::Mat str= h.stretch(image,0.01f);
// Show the result
cv::namedWindow("Stretched Image");
cv::imshow("Stretched Image",str);
// Show the new histogram
cv::namedWindow("Stretched Histogram");
cv::imshow("Stretched Histogram",h.getHistogramImage(str));
// Create an image inversion table
int dim(256);
cv::Mat lut(1, // 1 dimension
&dim, // 256 entries
CV_8U); // uchar
// or cv::Mat lut(256,1,CV_8U);
for (int i=0; i<256; i++) {
lut.at<uchar>(i)= 255-i;
}
// Apply lookup and display negative image
cv::namedWindow("Negative image");
cv::imshow("Negative image",h.applyLookUp(image,lut));
cv::waitKey();
return 0;
}示例3: main_his
int main_his()
{
// Read input image
cv::Mat image= cv::imread("Koala.jpg",0);
if (!image.data)
return 0;
// Display the image
cv::namedWindow("Image");
cv::imshow("Image",image);
// The histogram object
Histogram1D h;
// Compute the histogram
cv::MatND histo= h.getHistogram(image);
// Loop over each bin
for (int i=0; i<256; i++)
cout << "Value " << i << " = " << histo.at<float>(i) << endl;
// Display a histogram as an image
cv::namedWindow("Histogram");
cv::imshow("Histogram",h.getHistogramImage(image));
// creating a binary image by thresholding at the valley
cv::Mat thresholded;
cv::threshold(image,thresholded,60,255,cv::THRESH_BINARY);
// Display the thresholded image
cv::namedWindow("Binary Image");
cv::imshow("Binary Image",thresholded);
cv::imwrite("binary.bmp",thresholded);
// Equalize the image
cv::Mat eq= h.equalize(image);
// Show the result
cv::namedWindow("Equalized Image");
cv::imshow("Equalized Image",eq);
// Show the new histogram
cv::namedWindow("Equalized Histogram");
cv::imshow("Equalized Histogram",h.getHistogramImage(eq));
// Stretch the image ignoring bins with less than 5 pixels
cv::Mat str= h.stretch(image,5);
// Show the result
cv::namedWindow("Stretched Image");
cv::imshow("Stretched Image",str);
// Show the new histogram
cv::namedWindow("Stretched Histogram");
cv::imshow("Stretched Histogram",h.getHistogramImage(str));
// Create an image inversion table
//uchar lookup[256];
// Create lookup table
int dims[1]={256};
cv::MatND lookup(1,dims,CV_8U);
for (int i=0; i<256; i++) {
lookup.at<uchar>(i)=255-i;
}
// Apply lookup and display negative image
cv::namedWindow("Negative image");
cv::imshow("Negative image",h.applyLookUp(image,lookup));
cv::waitKey();
return 0;
}