【openCV在QTcreater实现图像的几种变换包括灰度二值变换、伽马HSV等变换源码】

效果如图

主要是三个代码，如下图

Table of Contents

main.cpp

#include "mainwindow.h"

#include <QApplication>

int main(int argc, char *argv[])
{
    QApplication a(argc, argv);

//    MainWindow w;
//    w.show();

    Mat img=imread("C:/Users/57281/Pictures/cc3.jpg");

//    namedWindow( "Display window", WINDOW_AUTOSIZE );
//    imshow("Display window", img);

    originalpicture(img);
    grayShow(img);

    logTransfer(img);
    gammaTranfer(img);
    colorTransfer(img);

    return a.exec();
}

pro文件

项目文件pro

QT       += core gui

greaterThan(QT_MAJOR_VERSION, 4): QT += widgets

CONFIG += c++17

# You can make your code fail to compile if it uses deprecated APIs.
# In order to do so, uncomment the following line.
#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0

SOURCES += \
    main.cpp

HEADERS +=

# Default rules for deployment.
qnx: target.path = /tmp/$${TARGET}/bin
else: unix:!android: target.path = /opt/$${TARGET}/bin
!isEmpty(target.path): INSTALLS += target

INCLUDEPATH += D:\applearn\Opencv-VC\opencv\newbuild-me\install\include
LIBS += D:\applearn\Opencv-VC\opencv\newbuild-me\lib\libopencv_*.a

mainwindow.h文件

mainwindow.h文件函数定义等

#ifndef MAINWINDOW_H
#define MAINWINDOW_H

#include <QMainWindow>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;

//ctrl+i快捷键自动对齐==声明函数
void originalpicture(Mat &image);
void grayShow(Mat &image);
void Threshold2(Mat &gray);
void logTransfer(Mat &gray);
void gammaTranfer(Mat &gray);
void colorTransfer(Mat &image);

//原始图像
void originalpicture(Mat &image)
{
    Mat img;
    img=image;
    namedWindow( "Origin window");
    imshow("Origin window", img);
}

//灰度图像
void grayShow(Mat &image)
{
    Mat gray;
    cvtColor(image, gray, COLOR_RGBA2GRAY);
    namedWindow("gray picture");
    imshow("gray picture", gray);
    //    namedWindow( "Display window", WINDOW_AUTOSIZE );
    Threshold2(gray);
    //logTransfer(gray);
    //gammaTranfer(gray);
}

//二值变换
void Threshold2(Mat &gray)
{
    Mat result;
    threshold(gray, result, 120,255,THRESH_BINARY);
    namedWindow("binary picture");
    imshow("binary picture", result);
}

//对数变换
void logTransfer(Mat &gray)
{
    Mat srcImage(gray);
    Mat dstImage(srcImage.size(),srcImage.type());
    //计算1+r
    add(gray, Scalar(8), srcImage);
    //转换为浮点数
    srcImage.convertTo(srcImage, CV_64F);
    //计算log(1+r) log:第一个参数为输入图像，第二个参数为得到的对数值
    log(srcImage,dstImage);
    dstImage=1*dstImage;
    //归一化处理
    normalize(dstImage,dstImage,0,255,NORM_MINMAX);
    convertScaleAbs(dstImage, dstImage);
    imshow("dstpicture", dstImage);
}

//伽马变换
void gammaTranfer(Mat &gray)
{
    //gamma值，随着值不同图片呈现出不同的效果
    double gamma=0.5;
    Mat grayImg;
    gray.convertTo(grayImg, CV_64F,1.0/255,0);
    Mat gammaImg;
    pow(grayImg, gamma,gammaImg);
    gammaImg.convertTo(gammaImg, CV_8U,255,0);
    imshow("gammapicture", gammaImg);
}

//彩色图像变换
void colorTransfer(Mat &image)
{
    Mat colorpicture;
    image.copyTo(colorpicture);
   //HSV
    Mat hsvImg;
    cvtColor(image,hsvImg, COLOR_BGR2HSV);
    std::vector<Mat> hsv;
    split(hsvImg, hsv);
    hsv[0]=(Scalar::all(180)-hsv[0]);
    merge(hsv, colorpicture);
    imshow("HSV_picture", colorpicture);
  //RGB
    colorpicture=Scalar::all(255)-image;
    imshow("RBG_picture", colorpicture);
}

//int main(int argc, char** argv) {
//    //读取图像
//    Mat image;
//    image = imread("/Users/Admin/Desktop/myProject/1.jpg", 1);
//    namedWindow("Display Image", WINDOW_AUTOSIZE);
//    imshow("Display Image", image);
//    //grayShow(image);
//    colorTransfer(image);
//    waitKey(0);
//    return 0;
//}

class MainWindow : public QMainWindow
{
    Q_OBJECT

public:
    MainWindow(QWidget *parent = nullptr);
    ~MainWindow();
};
#endif // MAINWINDOW_H

结果处理

一些参考来源：
1、https://blog.csdn.net/chuxuezheerer/article/details/106322311
2、https://blog.csdn.net/dongbao520/article/details/124618235[0]

一些备注

normalize()函数：

    src 输入数组
    dst 输出数组，支持原地运算
    range normalization模式的最小值
    range normalization模式的最大值，不用于norm normalization(范数归一化)模式。
    normType归一化的类型，可以有以下的取值：
    – NORM_MINMAX:数组的数值被平移或缩放到一个指定的范围，线性归一化，一般较常用。
    –NORM_INF: 此类型的定义没有查到，根据OpenCV 1的对应项，可能是归一化数组的C-范数(绝对值的最大值)
    –NORM_L1 : 归一化数组的L1-范数(绝对值的和)
    –NORM_L2: 归一化数组的(欧几里德)L2-范数