OpenCV + CPP 系列（八）影像的加權混合 、對比度與亮度

一、影像的加權混合

線性混合

函式是將兩張相同大小，相同型別的圖片（疊加）線性融合的函式，可以實作圖片的特效，

影像的線性混合： g ( x ) = ( 1 ? α ) f 0 ( x ) + α f 1 ( x ) \mathrm{g}(x) = (1- \alpha)f_0(x)+ \alpha f_1(x) g(x)=(1?α)f0?(x)+αf1?(x)

void addWeighted(

InputArray src1,　　 　原陣列1
double alpha, 　　　　原陣列1的權重值 : α \alpha α
InputArray src2,　　　原陣列2
double beta, 　　　　 陣列２ 的權重值，( 1 ? α 1-\alpha 1?α)
double gamma, 　　 加權和后的影像的偏移量(標量)
OutputArray dst, 　　輸出的陣列（公式如上）
int dtype = -1　　　　輸出陣列的深度，有默認值-1，即src1.depth()
);

頭檔案 quick_opencv.h：宣告類與公共函式

#pragma once
#include <opencv2\opencv.hpp>
using namespace cv;

class QuickDemo {
public:
	...
	void mix_image_Demo(Mat& image1, Mat& image2);  //新增方法
	void image_contrast_Demo(Mat& image1);

};

主函式呼叫該類的公共成員函式

#include <opencv2\opencv.hpp>
#include <quick_opencv.h>
#include <iostream>
using namespace cv;


int main(int argc, char** argv) {
	Mat src1 = imread("D:\\Desktop\\ttt.png");
	Mat src2 = imread("D:\\Desktop\\uuu.png");
	if (src1.empty()) {
		printf("Could not load images1...\n");
		return -1;
	}
	if (src2.empty()) {
		printf("Could not load images2...\n");
		return -1;
	}
	imshow("input1", src1);
	imshow("input2", src2);

	QuickDemo qk;
	qk.mix_image_Demo(src1, src2);
	qk.image_contrast_Demo(src1);
	waitKey(0);
	destroyAllWindows();
	return 0;
}

源檔案 quick_demo.cpp：實作類與公共函式

#include <quick_opencv.h>
#include <opencv2/dnn.hpp>
using namespace cv;
using namespace std;


void QuickDemo::mix_image_Demo(Mat& image1, Mat& image2) {
	double alpha = 0.5;
	if (image1.size() != image2.size()) {
		cout << "影像尺寸不匹配" << endl;
	}
	Mat dst;
	addWeighted(image1, alpha, image2, (1 - alpha), 0, dst, -1);
	imshow("dst", dst);
}

二、對比度增強

通過影像的像素變換（點操作）調整影像的亮度和對比度：
g ( i , j ) = α f ( i , j ) + β \mathrm{g}(i,j) = \alpha f(i,j)+ \beta g(i,j)=αf(i,j)+β 其中 β \beta β 為增益變數

源檔案 quick_demo.cpp：實作類與公共函式

void QuickDemo::image_contrast_Demo(Mat& image) {
	int width = image.cols;
	int height = image.rows;
	int channel = image.channels();
	Mat dst_at = Mat::zeros(image.size(), image.type());
	Mat dst_ptr = dst_at.clone();
	float alpha = 1.5;
	float beta = 10.0;

	//轉成灰度圖，浮點數圖（計算精度更高），
	Mat image32f,image8u;
	cvtColor(image.clone(), image8u, COLOR_BGR2GRAY);
	image.convertTo(image32f, CV_32F);

	Mat dst_8u = Mat::zeros(image8u.size(), image8u.type());
	int channel8u = image8u.channels();
	if (channel8u == 1) {
		for (int h = 0; h < height; h++) {
			for (int w = 0; w < width; w++) {
				uchar v = image8u.at<uchar>(h, w);
				dst_8u.at<uchar>(h, w) = saturate_cast<uchar>(v * alpha + beta);
			}
		}
	}
	double time0 = static_cast<double>(getTickCount()); // 計時
	if (channel == 3) {
		for (int h = 0; h < height; h++) {
			for (int w = 0; w < width; w++) {
				dst_at.at<Vec3b>(h, w)[0] = saturate_cast<uchar>(image32f.at<Vec3f>(h, w)[0] * alpha + beta);
				dst_at.at<Vec3b>(h, w)[1] = saturate_cast<uchar>(image32f.at<Vec3f>(h, w)[1] * alpha + beta);
				dst_at.at<Vec3b>(h, w)[2] = saturate_cast<uchar>(image32f.at<Vec3f>(h, w)[2] * alpha + beta);
			}
		}
	}
	double time1 = static_cast<double>(getTickCount());  // 計時
	if (channel == 3) {
		for (int h = 0; h < height; h++) {
			float* current_row = image32f.ptr<float>(h);
			uchar* dst_current_row = dst_ptr.ptr<uchar>(h);
			for (int w = 0; w < width; w++) {
				*dst_current_row++ = saturate_cast<uchar>(*current_row++ * alpha + beta);
				*dst_current_row++ = saturate_cast<uchar>(*current_row++ * alpha + beta);
				*dst_current_row++ = saturate_cast<uchar>(*current_row++ * alpha + beta);
			}
		}
	}
	double time2 = static_cast<double>(getTickCount());  // 計時
	cout << "time1-time0=" << (time1 - time0)/getTickFrequency() << endl;
	cout << "time2-time1=" << (time2 - time1)/ getTickFrequency() << endl;
	imshow("image8u原圖", image8u);
	imshow("image8u對比度增強at", dst_8u);
	imshow("image對比度增強at", dst_at);
	imshow("image對比度增強ptr", dst_ptr);
}

兩種像素對比度增強，使用at與ptr兩種像素遍歷方式，ptr遍歷方式速度大約快一半，(單位：秒)

關于手動調節 亮度與對比對，