Homogeneous Blur

Homogeneous Blur is the most simplest method of smoothing an image. It is also called as Homogeneous Smoothing, Homogeneous Filtering and Box Blurring. In this technique, each pixel value is calculated as the average value of the neighborhood of the pixel defined by the kernel.

Kernels used in the homogeneous blur is called normalized box filter. You may define any size for this kernel according to  your requirement. But it is preferable to define square kernels with a size of odd width and height. In the following images, I have shown 3 x 3 and 5 x 5 normalized box filters.
3x3 Normalized box filter
3x3 Normalized box filter


5 x 5 Normalized box filter
5 x 5 Normalized box filter


You have to choose a right size of the kernel to define the neighborhood of each pixel. If it is too large, small features of the image may be disappeared and the image will look blurred. If it is too small, you cannot eliminate noises in the image.


Homogeneous Blur on Images with OpenCV


This is how you blur/smooth an image with OpenCV. You may choose the size of the kernel according to your requirement. I have used 3 x 3 and 5 x 5 kernel for this example program.

//Uncomment the following line if you are compiling this code in Visual Studio
//#include "stdafx.h"

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
    // Read the image file
    Mat image = imread("D:/My OpenCV Website/Lady with a Guitar.jpg");

    // Check for failure
    if (image.empty())
    {
        cout << "Could not open or find the image" << endl;
        cin.get(); //wait for any key press
        return -1;
    }

    //Blur the image with 3x3 kernel
    Mat image_blurred_with_3x3_kernel;
    blur(image, image_blurred_with_3x3_kernel, Size(3, 3));

    //Blur the image with 5x5 kernel
    Mat image_blurred_with_5x5_kernel;
    blur(image, image_blurred_with_5x5_kernel, Size(5, 5));

    //Define names of the windows
    String window_name = "The Guitar"; 
    String window_name_blurred_with_3x3_kernel = "The Guitar Blurred with 3 x 3 Kernel";
    String window_name_blurred_with_5x5_kernel = "The Guitar Blurred with 5 x 5 Kernel";

    // Create windows with above names
    namedWindow(window_name);
    namedWindow(window_name_blurred_with_3x3_kernel);
    namedWindow(window_name_blurred_with_5x5_kernel);

    // Show our images inside the created windows.
    imshow(window_name, image); 
    imshow(window_name_blurred_with_3x3_kernel, image_blurred_with_3x3_kernel);
    imshow(window_name_blurred_with_5x5_kernel, image_blurred_with_5x5_kernel);

    waitKey(0); // Wait for any keystroke in the window

    destroyAllWindows(); //destroy all opened windows

    return 0;
}

Copy and paste the above code snippet into your IDE and run it. Please note that you have to replace "D:/My OpenCV Website/Lady with a Guitar.jpg" in the code with a valid location to an image in your computer. Then you should see a set of images like the below.

Original Image
Original Image

Image blurred with 3 x 3 normalized box filter
Image blurred with 3 x 3 normalized box filter

Image blurred with 5 x 5 normalized box filter
Image blurred with 5 x 5 normalized box filter



Explanation


Let's go through the above OpenCV program line by line.


// Read the image file
Mat image = imread("D:/My OpenCV Website/Lady with a Guitar.jpg");

// Check for failure
if (image.empty())
{
    cout << "Could not open or find the image" << endl;
    cin.get(); //wait for any key press
    return -1;
}
This code segment loads an image from the file "D:/My OpenCV Website/Lady with a Guitar.jpg" and returns it as a Mat object.
If the returned Mat object is empty, exit the program by returning from the main function. This is an important check because calling imshow() on empty Mat object might crash your program.



//Blur the image with 3x3 kernel
Mat image_blurred_with_3x3_kernel;
blur(image, image_blurred_with_3x3_kernel, Size(3, 3));
The above function performs the homogeneous smoothing/blur operation with a 3 x 3 normalized box filter on the original image and stores the smoothed image in the image_blurred_with_3x3_kernel Mat object. Each channel in the original image is processed independently.


//Blur the image with 5x5 kernel
Mat image_blurred_with_5x5_kernel;
blur(image, image_blurred_with_5x5_kernel, Size(5, 5));
The above function performs the homogeneous smoothing/blur operation with a 5 x 5 normalized box filter on the original image and stores the smoothed image in the image_blurred_with_5x5_kernel Mat object. Each channel in the original image is processed independently.


//Define names of the window
String window_name = "The Guitar"; 
String window_name_blurred_with_3x3_kernel = "The Guitar Blurred with 3 x 3 Kernel";
String window_name_blurred_with_5x5_kernel = "The Guitar Blurred with 5 x 5 Kernel";

// Create a window with above names
namedWindow(window_name);
namedWindow(window_name_blurred_with_3x3_kernel);
namedWindow(window_name_blurred_with_5x5_kernel);

// Show our images inside the created windows.
imshow(window_name, image); 
imshow(window_name_blurred_with_3x3_kernel, image_blurred_with_3x3_kernel);
imshow(window_name_blurred_with_5x5_kernel, image_blurred_with_5x5_kernel);
The above code segment creates windows and shows images in them.


waitKey(0); // Wait for any keystroke in the window

destroyAllWindows(); //destroy all opened windows
The program waits for any keystroke. After any key is pressed, all opened windows will be destroyed.


Summary


In the above section, you have learned,
  • How to load an image from a file
  • How to perform the homogeneous smoothing/blur operation on images with a normalized box filter.
  • How to create windows and display images
  • How to wait without exiting the program until the user presses a key
  • How to destroy created windows


Homogeneous Blur on Videos with OpenCV


Now I am going to show you how to blur/smooth a video using an OpenCV C++ example. This is pretty much similar to the previous example.

It is recommended to go through the Play Video from File or Camera first in order to understand the following example better.


//Uncomment the following line if you are compiling this code in Visual Studio
//#include "stdafx.h"

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main(int argc, char* argv[])
{
    //open the video file for reading
    VideoCapture cap("D:/My OpenCV Website/A Herd of Deer Running.mp4");

    // if not success, exit program
    if (cap.isOpened() == false)
    {
        cout << "Cannot open the video file" << endl;
        cin.get(); //wait for any key press
        return -1;
    }



    //Define names of the window
    String window_name_of_original_video = "Original Video";
    String window_name_of_video_blurred_with_5x5_kernel = "Video Blurred with 5 x 5 Kernel";

    // Create a window with above names
    namedWindow(window_name_of_original_video, WINDOW_NORMAL);
    namedWindow(window_name_of_video_blurred_with_5x5_kernel, WINDOW_NORMAL);

    while (true)
    {
        Mat frame;
        bool bSuccess = cap.read(frame); // read a new frame from video 
        if (bSuccess == false)
        {
            cout << "Found the end of the video" << endl;
            break;
        }

        //Blur the frame with 5x5 kernel
        Mat frame_blurred_with_5x5_kernel;
        blur(frame, frame_blurred_with_5x5_kernel, Size(5, 5));

        //show the frames in the created windows
        imshow(window_name_of_original_video, frame);
        imshow(window_name_of_video_blurred_with_5x5_kernel, frame_blurred_with_5x5_kernel);

        //wait for for 10 ms until any key is pressed.  
        //If the 'Esc' key is pressed, break the while loop.
        //If the any other key is pressed, continue the loop 
        //If any key is not pressed withing 10 ms, continue the loop
        if (waitKey(10) == 27)
        {
            cout << "Esc key is pressed by user. Stoppig the video" << endl;
            break;
        }
    }

    return 0;

}
Copy and paste the above code snippet into your IDE and run it. Please note that you have to replace "D:/My OpenCV Website/A Herd of Deer Running.mp4" in the code with a valid location to a video in your computer. Then you should see a smoothed/blurred video along with the original video.


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