OpenCV  3.1.0 Open Source Computer Vision
Adding (blending) two images using OpenCV

## Goal

In this tutorial you will learn:

• what is linear blending and why it is useful;

## Theory

Note
The explanation below belongs to the book Computer Vision: Algorithms and Applications by Richard Szeliski

From our previous tutorial, we know already a bit of Pixel operators. An interesting dyadic (two-input) operator is the linear blend operator:

$g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)$

By varying $$\alpha$$ from $$0 \rightarrow 1$$ this operator can be used to perform a temporal cross-dissolve between two images or videos, as seen in slide shows and film productions (cool, eh?)

## Code

As usual, after the not-so-lengthy explanation, let's go to the code:

#include <opencv2/opencv.hpp>
#include <iostream>
using namespace cv;
int main( int argc, char** argv )
{
double alpha = 0.5; double beta; double input;
Mat src1, src2, dst;
std::cout<<" Simple Linear Blender "<<std::endl;
std::cout<<"-----------------------"<<std::endl;
std::cout<<"* Enter alpha [0-1]: ";
std::cin>>input;
if( input >= 0.0 && input <= 1.0 )
{ alpha = input; }
namedWindow("Linear Blend", 1);
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
imshow( "Linear Blend", dst );
waitKey(0);
return 0;
}

## Explanation

1. Since we are going to perform:

$g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)$

We need two source images ( $$f_{0}(x)$$ and $$f_{1}(x)$$). So, we load them in the usual way:

warning

Since we are adding src1 and src2, they both have to be of the same size (width and height) and type.

2. Now we need to generate the g(x) image. For this, the function add_weighted:addWeighted comes quite handy:
beta = ( 1.0 - alpha );
addWeighted( src1, alpha, src2, beta, 0.0, dst);
$dst = \alpha \cdot src1 + \beta \cdot src2 + \gamma$
In this case, gamma is the argument $$0.0$$ in the code above.