OST.zip_图像处理

#include "mainwindow.h" #include "ui_mainwindow.h" #include <QTime> #include <QBuffer> #include <QDebug> #include <qstring.h> #include <string> #include <QSlider> #include <QtCore/QVariant> #include <QAction> #include <QHeaderView> MainWindow::MainWindow(QWidget *parent) : QMainWindow(parent), ui(new Ui::MainWindow) { ui->setupUi(this); connect(ui->grayButton, SIGNAL(clicked()), this, SLOT(on_grayButton_clicked())); connect(ui->filterButton, SIGNAL(clicked()), this, SLOT(on_filterButton_clicked())); connect(ui->contourButton, SIGNAL(clicked()), this, SLOT(on_contourButton_clicked())); } MainWindow::~MainWindow() { delete ui; } void MainWindow::on_pushButton_clicked() { QFileDialog::Options options; QString selectedFilter; QString fileName = QFileDialog::getOpenFileName(this, tr("Open Image Files"), "", tr("Image files (*.jpeg *.jpg *.png *.gif *.bmp)"), &selectedFilter, options); if (!fileName.isEmpty()){ sourceimage = cv::imread(fileName.toStdString(),1);} //0 for grayscale，注意这里如果是0的话可能是打开灰度形式的 else { return; } sourceimage.copyTo(image1); displayMat1(sourceimage); } void MainWindow::displayMat1(const cv::Mat& image) { //BGR openCV Mat to QImage QImage img_qt = QImage((const unsigned char*)image.data,image.cols, image.rows, image.step, QImage::Format_RGB888); //For Binary Images if (img_qt.isNull()){ //ColorTable for Binary Images QVector<QRgb> colorTable; for (int i = 0; i < 256; i++) colorTable.push_back(qRgb(i, i, i)); img_qt = QImage((const unsigned char*)image.data,image.cols, image.rows, QImage::Format_RGB888);// QImage::Format_Indexed8 img_qt.setColorTable(colorTable); } //Display the QImage in the Label QPixmap img_pix = QPixmap::fromImage(img_qt.rgbSwapped()); // RGB to BGR 然后用QPixmap对象获取图像 ui->label->resize(img_pix.size()); ui->label->setPixmap(img_pix.scaled(ui->label->size(), Qt::KeepAspectRatio)); //ui->label_12->resize(ui->label_12->pixmap()->size()); //this->ui->label_12->setPixmap(img_pix); } void MainWindow::on_pushButton_2_clicked()//转换成HSI图像并分离 { src = cvCloneImage(&(IplImage)sourceimage);//原图像转换成 IplImage *src copyimg= cvCreateImage(cvGetSize(src),8,3); //建立一个图像 8位3通道 cvCopy(src,copyimg,NULL); //将原图拷贝一份 hsi = cvCreateImage(cvGetSize(src),8,3); h_plane = cvCreateImage(cvGetSize(src),8,1); s_plane = cvCreateImage(cvGetSize(src),8,1); i_plane = cvCreateImage(cvGetSize(src),8,1); cvCvtColor( copyimg, hsi, CV_BGR2HSV );//将RGB转换成HSI空间 cvSplit(hsi,h_plane,s_plane,i_plane, NULL);//将HSI图像分解成三个分量 cvNamedWindow( "1", CV_WINDOW_AUTOSIZE ); cvShowImage("1",hsi); cvNamedWindow( "2", CV_WINDOW_AUTOSIZE ); cvShowImage("2",h_plane); cvNamedWindow( "3", CV_WINDOW_AUTOSIZE ); cvShowImage("3",s_plane); cvNamedWindow( "4", CV_WINDOW_AUTOSIZE ); cvShowImage("4",i_plane); } void MainWindow::on_grayButton_clicked() { src = cvCloneImage(&(IplImage)sourceimage); IplImage *img1 = cvCreateImage(cvGetSize(src),8,1); cvCvtColor(src,img1,CV_BGR2GRAY);//灰度化 cvNamedWindow( "1", CV_WINDOW_AUTOSIZE ); cvShowImage("1",img1); } void MainWindow::on_filterButton_clicked() { src = cvCloneImage(&(IplImage)sourceimage); IplImage *img2 = cvCreateImage(cvGetSize(src),8,3); cvSmooth(src,img2,CV_MEDIAN,5,3);//均值滤波 cvNamedWindow( "1", CV_WINDOW_AUTOSIZE ); cvShowImage("1",img2); } void MainWindow::on_contourButton_clicked() { src = cvCloneImage(&(IplImage)sourceimage); height=src->height; width=src->width; size = height * width; //histogram float histogram[256]={0}; for( m=0; m < height; m++) { unsigned char* p=(unsigned char*)src->imageData + src->widthStep * m; for(0; n < width; n++) { histogram[int(*p++)]++; } } sum0 = 0; sum1 = 0; //存储前景的灰度总和和背景灰度总和 cnt0 = 0; cnt1 = 0; //前景的总个数和背景的总个数 w0 = 0; w1 = 0; //前景和背景所占整幅图像的比例 u0 = 0; u1 = 0; //前景和背景的平均灰度 variance = 0; //最大类间方差 u = 0; maxVariance = 0; for(i = 1; i < 256; i++) //一次遍历每个像素 { sum0 = 0; sum1 = 0; cnt0 = 0; cnt1 = 0; w0 = 0; w1 = 0; for(j = 0; j < i; j++) { cnt0 += histogram[j]; sum0 += j * histogram[j]; } u0 = (double)sum0 / cnt0; w0 = (double)cnt0 / size; for(j = i ; j <= 255; j++) { cnt1 += histogram[j]; sum1 += j * histogram[j]; } u1 = (double)sum1 / cnt1; w1 = 1 - w0; // (double)cnt1 / size; u = u0 * w0 + u1 * w1; //图像的平均灰度 printf("u = %f\n", u); //variance = w0 * pow((u0 - u), 2) + w1 * pow((u1 - u), 2); variance = w0 * w1 * (u0 - u1) * (u0 - u1); if(variance > maxVariance) { maxVariance = variance; threshold = i; } } printf("threshold = %d\n", threshold); cvThreshold(src, dst, threshold, 255, CV_THRESH_BINARY); cvNamedWindow( "src", 1 ); cvShowImage("src", dst); cvWaitKey(-1); cvReleaseImage(&src); cvReleaseImage(&dst); cvDestroyWindow( "dst" ); return 0; }