TIL Day 22

2023.10.19

Today's agenda

1. Image brightness / constrast
2. Histogran analysis

1. Image brighness / contrast

Image brightness

#include <iostream>
#include "opencv2/opencv.hpp"

using namesapce std;
using namespace cv;

int main(){
	Mat src = imread("lenna.bmp", IMREAD_GREYSCALE);
    
    if(src.empty()){
    	cerr << "Image load failed" << "\n";
    }
    
    Mat dst1 = src - Scalar(50);		// darker
    add(src, 50, dst1);					// darker(same result)
    Mat dst2 = src + Scalar(50);		// brighter
    add(src, -50, dst2)					// brighter(same result)
    Mat dst3 = Scalar(255) - src;		// inverse image
    
    imshow("src", src);
    imshow("dst1", dst1);
    imshow("dst2", dst2);
    imshow("dst3", dst3);
    waitKey();
}

If want to change brightness of the image just simple function you have
but in color image, - + operator just can not change the brightness. because color image has 3 or 4 channels for presents color. if you want to change brightness in color image, Scalar must needed.

Image contrast

#include <iostream>
#include "opencv2/opencv.hpp"

using namesapce std;
using namespace cv;

int main(){
	Mat src = imread("lenna.bmp", IMREAD_GREYSCALE);
    
    if(src.empty()){
    	cerr << "Image load failed" << "\n";
    }
    
    float alpha = 1.0f;
    int m = (int)mean(src)[0];
    Mat dst = src + (src - m) * alpha;
    
    imshow("src", src);
    imshow("dst", dst);
    waitKey();
}

In this sample code, given alpha value is 1.0f. But this method is not quite run a good result.
Actually get good constrast image is get m(average constrat value) in image and give a line to (m, m) line

2. Histogram analysis

Histogram : Given image's pixel distribution present to such a graph
but histogram can not get each pixel's location

#include <iostream>
#include "opencv2/opencv.hpp"

using namespace std;
using namespace cv;

Mat calcGrayHist(const Mat& img)
{
	CV_Assert(img.type() == CV_8U);

	Mat hist;
	int channels[] = { 0 };
	int dims = 1;
	const int histSize[] = { 256 };
	float graylevel[] = { 0, 256 };
	const float* ranges[] = { graylevel };

	calcHist(&img, 1, channels, noArray(), hist, dims, histSize, ranges);

	return hist;
}

Mat getGrayHistImage(const Mat& hist)
{
	CV_Assert(hist.type() == CV_32FC1);
	CV_Assert(hist.size() == Size(1, 256));

	double histMax = 0.;
	minMaxLoc(hist, 0, &histMax);

	Mat imgHist(100, 256, CV_8UC1, Scalar(255));
	for (int i = 0; i < 256; i++) {
		line(imgHist, Point(i, 100),
			Point(i, 100 - cvRound(hist.at<float>(i, 0) * 100 / histMax)), Scalar(0));
	}

	return imgHist;
}

int main()
{
	Mat src = imread("lenna.bmp", IMREAD_GRAYSCALE);

	if (src.empty()) {
		cerr << "Image load failed!" << endl;
		return -1;
	}

	Mat hist = calcGrayHist(src);
	Mat imgHist = getGrayHistImage(hist);

	imshow("src", src);
	imshow("hist", imgHist);

	waitKey();
}

Histogram stretching / equalization

#include <iostream>
#include "opencv2/opencv.hpp"

using namespace std;
using namespace cv;

Mat calcGrayHist(const Mat& img)
{
	CV_Assert(img.type() == CV_8U);

	Mat hist;
	int channels[] = { 0 };
	int dims = 1;
	const int histSize[] = { 256 };
	float graylevel[] = { 0, 256 };
	const float* ranges[] = { graylevel };

	calcHist(&img, 1, channels, noArray(), hist, dims, histSize, ranges, true);

	return hist;
}

Mat getGrayHistImage(const Mat& hist)
{
	CV_Assert(!hist.empty());
	CV_Assert(hist.type() == CV_32F);

	double histMax = 0.;
	minMaxLoc(hist, 0, &histMax);

	Mat imgHist(100, 256, CV_8UC1, Scalar(255));
	for (int i = 0; i < 256; i++) {
		line(imgHist, Point(i, 100),
			Point(i, 100 - cvRound(hist.at<float>(i) * 100 / histMax)), Scalar(0));
	}

	return imgHist;
}

int main()
{
	Mat src = imread("lenna.bmp", IMREAD_GRAYSCALE);

	if (src.empty()) {
		cerr << "Image load failed!" << endl;
		return -1;
	}

	double gmin, gmax;
	minMaxLoc(src, &gmin, &gmax);

	Mat dst = (src - gmin) * 255 / (gmax - gmin);

	imshow("src", src);
	imshow("dst", dst);
	imshow("hist_src", getGrayHistImage(calcGrayHist(src)));
	imshow("hist_dst", getGrayHistImage(calcGrayHist(dst)));

	waitKey();
}