基于OpenCV和C++实现图像增强

直方图均衡化

int equalizeHist_func(Mat image)
{
	
	if (image.empty())
	{
		std::cout << "打开图片失败,请检查" << std::endl;
		return -1;
	}
	imshow("原图像", image);
	if (image.channels() == 3)
	{
		Mat imageRGB[3];
		split(image, imageRGB);
		for (int i = 0; i < 3; i++)
		{
			equalizeHist(imageRGB[i], imageRGB[i]);
		}
		merge(imageRGB, 3, image);
	}
	if (image.channels() == 1)
	{
		equalizeHist(image, image);
	}
	imshow("直方图均衡化图像增强效果", image);
	waitKey();
	return 0;
}

拉普拉斯算子

int Laplace(Mat image)
{
	
	if (image.empty())
	{
		std::cout << "打开图片失败,请检查" << std::endl;
		return -1;
	}
	imshow("原图像", image);
	Mat imageEnhance;
	Mat kernel = (Mat_<float>(3, 3) << 0, -1, 0, 0, 5, 0, 0, -1, 0);
	filter2D(image, imageEnhance, CV_8UC3, kernel);
	imshow("拉普拉斯算子图像增强效果", imageEnhance);
	waitKey();
	return 0;
}

伽马变换

int gamma(Mat image)
{
	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]);
		}
	}
	//归一化到0~255    
	normalize(imageGamma, imageGamma, 0, 255, CV_MINMAX);
	//转换成8bit图像显示    
	convertScaleAbs(imageGamma, imageGamma);
	imshow("原图", image);
	imshow("伽马变换图像增强效果", imageGamma);
	waitKey();
	return 0;
}