负面形象是完全黑色的

Negative image is completly black

本文关键字：黑色      更新时间：2023-10-16

这是我的代码，它使用OpenCV 2.4.5

Histogram1D.h 

#ifndef HISTOGRAM1D_H
#define HISTOGRAM1D_H
#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
class Histogram1D
{
public:
    Histogram1D();
    //Histogram generators
    MatND getHistogram(Mat );
    Mat getHistogramImage(Mat );
    //Generate Negative Image
    Mat applyLookup(Mat ,Mat );
    //Generate improved image with equalized histogram
    Mat equalize(Mat image);
private:
    int histSize[1];//Number of bins
    float hRanges[2];//Max and Min pixel values
    const float *ranges[1];
    int channels[1];//Only one channel will be used
};
#endif // HISTOGRAM1D_H

Histogram1D.cpp 

#include "Histogram1D.h"

Histogram1D::Histogram1D()
{
    histSize[0] = 256;
    hRanges[0] = 0.0;
    hRanges[1] = 255.0;
    ranges[0] = hRanges;
    channels[0] = 0;
}
MatND Histogram1D::getHistogram(Mat image)
{
    MatND hist;
    cv::calcHist(&image,1,channels,Mat(),hist,1,histSize,ranges);
    return hist;
}
Mat Histogram1D::getHistogramImage(Mat image)
{
    MatND histo = getHistogram(image);
    //Get minimum and maximum value bins
    double minVal = 0;
    double maxVal = 0;
    minMaxLoc(histo,&minVal,&maxVal,0,0);
    //Image on which to display histogram
    Mat histImage(histSize[0],histSize[0],CV_8U,Scalar(255));
    //Set highest point at 90% of nbins
    int hpt = static_cast<int>(0.9,histSize[0]);
    //Draw a vertical line for each bin
    for(int i=0;i<histSize[0];i++)
    {
        float binVal = histo.at<float>(i);
        int intensity = static_cast<int>(binVal*hpt/maxVal);
        line(histImage,Point(i,histSize[0]),Point(i,histSize[0]-intensity),Scalar::all(0));
    }
    return histImage;

}
Mat Histogram1D::applyLookup(Mat image,Mat lookup)
{
    Mat result;
    cv::LUT(image,lookup,result);
    return result;
}

Mat Histogram1D::equalize(Mat image)
{
    Mat result;
    cv::equalizeHist(image,result);
    return result;
}

HistogramMain.cpp 

#include "Histogram1D.h"
int main()
{
    Histogram1D h;
    Mat image = imread("C:/Users/Public/Pictures/Sample Pictures/Penguins.jpg",CV_LOAD_IMAGE_GRAYSCALE);
    cout << "Number of Channels: " << image.channels() << endl;
    namedWindow("Image");
    imshow("Image",image);

    Mat histogramImage = h.getHistogramImage(image);
    namedWindow("Histogram");
    imshow("Histogram",histogramImage);
    Mat thresholded;
    threshold(image,thresholded,60,255,THRESH_BINARY);
    namedWindow("Binary Image");
    imshow("Binary Image",thresholded);

    Mat negativeImage;
    int dim(256);
    negativeImage = h.applyLookup(image,Mat(1,&dim,CV_8U));
    namedWindow("Negative Image");
    imshow("Negative Image",negativeImage);

    Mat equalizedImage;
    equalizedImage = h.equalize(image);
    namedWindow("Equalized Image");
    imshow("Equalized Image",equalizedImage);

    waitKey(0);
    return 0;
}

当你运行这段代码，负图像是100%黑色!最神奇的是，如果你从HistogramMain.cpp中删除所有其他代码，但保留下面与负图像相关的代码，你将得到正确的负图像!为什么会这样?

我使用的是QT最新版本，使用VS 2010编译器。

Mat negativeImage;
    int dim(256);
    negativeImage = h.applyLookup(image,Mat(1,&dim,CV_8U));
    namedWindow("Negative Image");
    imshow("Negative Image",negativeImage);

您的主要困难是表达式Mat(1,&dim,CV_8U)为cv::Mat分配内存，但没有初始化任何值。您的环境可能会用零填充未初始化的内存，这将解释调用applyLookup()后的黑色图像。在任何情况下，您都应该初始化查找表中的值，以便获得正确的结果。要反转图像，很容易:

int dim(256);
cv::Mat tab(1,&dim,CV_8U);
uchar* ptr = tab.ptr();
for (size_t i = 0; i < tab.total(); ++i)
{
    ptr[i] = 255 - i;
}

你的代码还有一些其他的问题:

行

int hpt = static_cast<int>(0.9,histSize[0]);

应为

int hpt = static_cast<int>(0.9*histSize[0]);

执行注释所指示的操作。注意你的编译器警告!

你的直方图范围也有问题

顺便说一下，使用opencv2图像现在是numpy数组，所以要在python中负一个灰色的8位图像，只需:

img = 255 - img
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