3.4 Gamma校正+對數Log變換

Gamma校正是對輸入圖像灰度值進行的非線性操作，使輸出圖像灰度值與輸入圖像灰度值呈指數關系：

A是一個常數，通常取1，這個指數即為Gamma。

Gamma校正的原理很簡單，就一個很簡單的表達式，如下圖所示：

其中V_in的取值范圍是0~1，最重要的參數就是公式中的γ參數！

γ的值決定了輸入圖像和輸出圖像之間的灰度映射方式，即決定了是增強低灰度值區域還是增高灰度值區域。
γ>1時，圖像的高灰度區域對比度得到增強。
γ<1時，圖像的低灰度區域對比度得到增強。
γ=1時，不改變原圖像。

伽馬變換對於圖像對比度偏低，並且整體亮度值偏高（對於於相機過曝）情況下的圖像增強效果明顯。

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

using namespace cv;

int main(int argc, char *argv[])
{
    Mat image = imread("D:\\Gamma校正.jpg");
    Mat imageGamma(image.size(), CV_32FC3);
    for (int i = 0; i < image.rows; i++)
    {
        for (int j = 0; j < image.cols; j++)
        {
            imageGamma.at<Vec3f>(i, j)[0] = (image.at<Vec3b>(i, j)[0])*(image.at<Vec3b>(i, j)[0])*(image.at<Vec3b>(i, j)[0]);
            imageGamma.at<Vec3f>(i, j)[1] = (image.at<Vec3b>(i, j)[1])*(image.at<Vec3b>(i, j)[1])*(image.at<Vec3b>(i, j)[1]);
            imageGamma.at<Vec3f>(i, j)[2] = (image.at<Vec3b>(i, j)[2])*(image.at<Vec3b>(i, j)[2])*(image.at<Vec3b>(i, j)[2]);
        }
    }
    //歸一化到0~255  
    normalize(imageGamma, imageGamma, 0, 255, CV_MINMAX);
    //轉換成8bit圖像顯示  
    convertScaleAbs(imageGamma, imageGamma);
    imshow("原圖", image);
    imshow("伽馬變換圖像增強效果", imageGamma);
    waitKey();
    return 0;
}

 

//////朱偉opencv圖像處理編程實例
#include <iostream>  
#include <opencv2\core\core.hpp>  
#include <opencv2\highgui\highgui.hpp>  
#include <opencv2\imgproc\imgproc.hpp>  
#include<cmath>
using namespace cv;

Mat gammaTransform(Mat &srcImage, float kFactor)
{

    unsigned char LUT[256];
    for (int i = 0; i < 256; i++)
    {
        float f = (i + 0.5f) / 255;
        f = (float)(pow(f, kFactor));
        LUT[i] = saturate_cast<uchar>(f*255.0f - 0.5f);
    }
    Mat resultImage = srcImage.clone();

    if (srcImage.channels() == 1)
    {

        MatIterator_<uchar> iterator = resultImage.begin<uchar>();
        MatIterator_<uchar> iteratorEnd = resultImage.end<uchar>();
        for (; iterator != iteratorEnd; iterator++)
        {
            *iterator = LUT[(*iterator)];
        }
    }
    else
    {


        MatIterator_<Vec3b> iterator = resultImage.begin<Vec3b>();
        MatIterator_<Vec3b> iteratorEnd = resultImage.end<Vec3b>();
        for (; iterator != iteratorEnd; iterator++)
        {
            (*iterator)[0] = LUT[((*iterator)[0])];//b
            (*iterator)[1] = LUT[((*iterator)[1])];//g
            (*iterator)[2] = LUT[((*iterator)[2])];//r
        }
    }
    return resultImage;
}
int main()
{
    Mat srcImage = imread("D:\\小女孩與熊.jpg");
    if (!srcImage.data)
    {
        printf("could not load image...\n");
        return -1;
    }
    //取兩種不同的gamma值
    float gamma1 = 3.33f;
    float gamma2 = 0.33f;
    float kFactor1 = 1 / gamma1;
    float kFactor2 = 1 / gamma2;
    Mat result1 = gammaTransform(srcImage, kFactor1);
    Mat result2 = gammaTransform(srcImage, kFactor2);
    imshow("srcImage", srcImage);
    imshow("res1", result1);
    imshow("res2", result2);
    waitKey(0);
    return 0;
}

 

對數Log變換:

對數變換對於整體對比度偏低並且灰度值偏低的圖像增強效果較好。

/////////////////////////////////////對數Log變換////////////////////////////////////////
////https://blog.csdn.net/dcrmg/article/details/53677739
#include <opencv2/highgui/highgui.hpp>    
#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;

int main(int argc, char *argv[])
{
    Mat image = imread("D:\\對數Log變換.jpg");
    Mat imageLog(image.size(), CV_32FC3);
    for (int i = 0; i < image.rows; i++)
    {
        for (int j = 0; j < image.cols; j++)
        {
            imageLog.at<Vec3f>(i, j)[0] = log(1 + image.at<Vec3b>(i, j)[0]);
            imageLog.at<Vec3f>(i, j)[1] = log(1 + image.at<Vec3b>(i, j)[1]);
            imageLog.at<Vec3f>(i, j)[2] = log(1 + image.at<Vec3b>(i, j)[2]);
        }
    }
    //歸一化到0~255  
    normalize(imageLog, imageLog, 0, 255, CV_MINMAX);
    //轉換成8bit圖像顯示  
    convertScaleAbs(imageLog, imageLog);
    imshow("Soure", image);
    imshow("after", imageLog);
    waitKey();
    return 0;
}

參考鏈接：

https://blog.csdn.net/linqianbi/article/details/78617615

https://blog.csdn.net/dcrmg/article/details/53677739

https://blog.csdn.net/lxy201700/article/details/24929013

其他：

https://www.cnblogs.com/qiqibaby/p/5325193.html 

https://www.cnblogs.com/lcchuguo/p/4052077.html