自動白平衡算法原理及結合Opencv的C++實現

算法原理

完美反射理論假設圖像中最亮的點就是白點，並以此白點爲參考對圖像進行自動白平衡，最亮點定義爲R+G+B的最大值。

算法過程

1.計算每個像素R,G,B之後，並保存
2.按照R+G+B的值的大小計算出其前10%或其他Ratio的白色參考點的閾值T
3.遍歷圖像中的每個點，計算其中R+G+B值大於T的所有點的R\G\B分量的累積和的平均值
4.將每個像素量化到[0, 255]

代碼實現

//////自動白平衡
int AutoBlance(Mat& src, Mat& dst)
{
	int ret = PreDealSource(src, dst);
	if (-1 == ret)
		return -1;
	vector<int>vHistRGB(767, 0);
	uchar iMaxVal = 0;
	int iSum = 0;
	uchar utemp;

	int nrows = src.rows;
	int ncols = src.cols;
	int jMax = ncols*src.channels();
 
	int i = 0;
	int j = 0;
	for (i = 0; i < nrows; i++)
	{
		uchar *psrc = src.ptr<uchar>(i);
		for (j = 0; j < jMax;)
		{
			iSum = 0;
			utemp = psrc[j++];
			iMaxVal = iMaxVal > utemp ? iMaxVal : utemp;
			iSum += utemp;
			utemp = psrc[j++];
			iMaxVal = iMaxVal > utemp ? iMaxVal : utemp;
			iSum += utemp;
			utemp = psrc[j++];
			iMaxVal = iMaxVal > utemp ? iMaxVal : utemp;
			iSum += utemp;
			vHistRGB[iSum]++;
		}
	}
	iSum = 0;
	int nsize = nrows*ncols;
	int iThreshLimit = static_cast<int>(nsize*0.1);
	int iThreshold = 0;
	for (i = 766; i >= 0; i--) 
	{
		iSum += vHistRGB[i];
		if (iSum > iThreshLimit) 
		{
			iThreshold = i;
			break;
		}
	}
	float AvgB = 0.0f;
	float AvgG = 0.0f;
	float AvgR = 0.0f;
	int cnt = 0;
	for (i = 0; i < nrows; i++)
	{
		uchar *psrc = src.ptr<uchar>(i);
		for (j = 0; j < jMax; j+=3)
		{
			int sumP = static_cast<int>(psrc[j])+ static_cast<int>(psrc[j+1]) + static_cast<int>(psrc[j+2]);
			if (sumP > iThreshold)
			{
				AvgB += static_cast<float>(psrc[j]);
				AvgG += static_cast<float>(psrc[j + 1]);
				AvgR += static_cast<float>(psrc[j + 2]);
				cnt++;
			}
		}
	}
	AvgB = cnt*iMaxVal / AvgB;
	AvgG = cnt*iMaxVal / AvgG;
	AvgR = cnt*iMaxVal / AvgR;
	for (i = 0; i < nrows; i++) 
	{
		uchar *psrc = src.ptr<uchar>(i);
		uchar *pdst = dst.ptr<uchar>(i);
		for (j = 0; j < jMax;) 
		{
			int Blue = static_cast<int>(psrc[j] * AvgB);
			Blue = Blue > 255 ? 255 : Blue;
			pdst[j] = static_cast<uchar>(Blue);
			j++;
			int Green = static_cast<int>(psrc[j] * AvgG);
			Green = Green > 255 ? 255 : Green;
			pdst[j] = static_cast<uchar>(Green);
			j++;
			int Red = static_cast<int>(psrc[j] * AvgR);
			Red = Red > 255 ? 255 : Red;
			pdst[j] = static_cast<uchar>(Red);
			j++;
		}
	}
	return 0;
}

#include<iostream>
#include <windows.h>
#include"ImageAlgorithm.h"
using namespace std;
/////測試程序
void testAutoBalance()
{
	Mat src = imread("E:\\AlgorithmImage\\autobalance2.jpg");
	Mat dst;
	int ret = AutoBlance(src, dst);
	/*if (0 == ret)
	{
		imshow("src", src);
		imshow("dst", dst);
		waitKey(0);
	}*/
}

//////主函數
int main()
{
	LARGE_INTEGER t1, t2, tc;
	QueryPerformanceFrequency(&tc);
	QueryPerformanceCounter(&t1);
//	testGrayWorld();
	testAutoBalance();
	QueryPerformanceCounter(&t2);
	printf("Use Time:%f\n", (t2.QuadPart - t1.QuadPart)*1.0 / tc.QuadPart);
	system("pause");
	return 0;
}

仿真條件

Opencv4.3.0
VS2015
CPU:AMD

圖像處理效果及時間

Debug：0.152
Release：0.009

Debug：0.154
Release：0.009

參考文獻

自動白平衡
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