实现白平衡算法中的灰度世界法,能有效改善图像发红/发蓝/发绿的现象
1、OpenCV
#include <opencv2/opencv.hpp>
using namespace cv;
int main()
{
Mat g_srcImage,dstImage;
vector<Mat> g_vChannels;
g_srcImage = imread("C:/Users/Administrator/Desktop/01.jpg");
imshow("原图",g_srcImage);
//waitKey(0);
//分离通道
split(g_srcImage, g_vChannels);
Mat imageBlueChannel = g_vChannels.at(0);
Mat imageGreenChannel = g_vChannels.at(1);
Mat imageRedChannel = g_vChannels.at(2);
double imageBlueChannelAvg = 0;
double imageGreenChannelAvg = 0;
double imageRedChannelAvg = 0;
//求各通道的平均值
imageBlueChannelAvg = mean(imageBlueChannel)[0];
imageGreenChannelAvg = mean(imageGreenChannel)[0];
imageRedChannelAvg = mean(imageRedChannel)[0];
//求出个通道所占增益
double K = (imageRedChannelAvg+imageGreenChannelAvg+imageRedChannelAvg) / 3;
double Kb = K / imageBlueChannelAvg;
double Kg = K / imageGreenChannelAvg;
double Kr = K / imageRedChannelAvg;
//更新白平衡后的各通道BGR值
addWeighted(imageBlueChannel,Kb,0,0,0,imageBlueChannel);
addWeighted(imageGreenChannel,Kg,0,0,0,imageGreenChannel);
addWeighted(imageRedChannel,Kr,0,0,0,imageRedChannel);
merge(g_vChannels,dstImage);//图像各通道合并
imshow("白平衡后图",dstImage);
waitKey(0);
return 0;
}
API详解:
void cvAddWeighted( const CvArr* src1, double alpha,const CvArr* src2, double beta,double gamma, CvArr* dst );
参数1:src1,图1
参数2:alpha,图1数组元素权重
参数3:src2,图2
参数4:beta,图2数组元素权重
参数5:gamma,图1与图2叠加之后再添加的数值。不要太大,不然图片一片白。总和等于255以上就是纯白色了。
参数6:dst,输出图片
即:目标图=src1*alpha+src2*beta+gamma
2、Halcon
dev_close_window ()
read_image (Image, 'D:/hellowprld/2/test777.jpg')
dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)
dev_display (Image)
*将图像进行通道分解,分别转换为三个通道的RGB图像
decompose3 (Image, Red, Green, Blue)
*实现白平衡算法中的灰度世界法,能有效改善图像发红/发蓝/发绿的现象
*取RGB各个通道的平均值
get_domain (Red, Domain)
intensity (Domain, Red, MeanRed, DeviationRed)
get_domain (Green, Domain)
intensity (Domain, Green, MeanGreen, DeviationGreen)
get_domain (Blue, Domain)
intensity (Domain, Blue, MeanBlue, DeviationBlue)
*求出个通道所占增益
K := (MeanRed + MeanGreen + MeanBlue) / 3.0
Kr := K / MeanRed
Kg := K / MeanGreen
Kb := K / MeanBlue
*更新白平衡后的各通道值White Balance
scale_image (Red, ImageScaledRed, Kr, 0)
scale_image (Green, ImageScaledGreen, Kg, 0)
scale_image (Blue, ImageScaledBlue, Kb, 0)
compose3(ImageScaledRed, ImageScaledGreen, ImageScaledBlue, Multichannel0)
write_image (Multichannel0, 'jpeg 100', 0, 'D:/opt.jpg')
stop()
---------------附录--------------------
两幅图像之间处理的算子
1.sub_image(ImageMinuend, ImageSubtrahend : ImageSub : Mult, Add : )
对两幅图像做减法 g' := (g1 - g2) * Mult + Add
程序如下:
read_image (Scene00, 'autobahn/scene_00')
read_image (Scene01, 'autobahn/scene_01')
sub_image (Scene00, Scene01, ImageSub1, 1, 0)
dev_display(ImageSub1)
2.abs_image(Image : ImageAbs : : )
计算图像的绝对值模型
3.crop_part(Image : ImagePart : Row, Column, Width, Height : )
剪切出一个长方形的图像
4.add_image(Image1, Image2 : ImageResult : Mult, Add : )
两图像相叠加 g' := (g1 + g2) * Mult + Add
5.max_image(Image1, Image2 : ImageMax : : )
计算两幅图像每个像素点的最大值
6.min_image(Image1, Image2 : ImageMin : : )
计算两幅图像每个像素点的最小值
7.div_image(Image1, Image2 : ImageResult : Mult, Add : )
两幅图像相除 g' := g1 / g2 * Mult + Add
8.mult_image(Image1, Image2 : ImageResult : Mult, Add : )
两幅图像相乘 g' := g1 * g2 * Mult + Add