Python CV2 Unblur

Python CV2 (OpenCV) is a library for computer vision programming in Python. This library is used to process images and video in order to extract information from them. One important aspect when working with images is image restoration. In this project, we will be discussing how to unblur an image using OpenCV in Python.

Requirements

To follow along with this project, you will need:

• Python 3.6 or higher
• OpenCV (cv2) library
• Numpy library

You can install the necessary libraries by using the following command:

!pip install opencv-python numpy

Steps

1. Import the necessary libraries: cv2 and numpy.

import cv2
import numpy as np

2. Load the image file that you want to unblur.

img = cv2.imread('image.jpg')

3. Convert the image to grayscale.

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

4. Apply a Gaussian blur to the grayscale image.

blur = cv2.GaussianBlur(gray, (5,5), 0)

5. Apply an unsharp mask to the blurred image.

unsharp_mask = cv2.addWeighted(gray, 2, blur, -1, 0)

6. Display the original and unblurred images side by side.

cv2.imshow('Original Image', img)
cv2.imshow('Unblurred Image', unsharp_mask)
cv2.waitKey(0)
cv2.destroyAllWindows()

Explanation

The above code uses a Gaussian blur to blur the image, and then applies an unsharp mask to the blurred image to unblur it. An unsharp mask works by subtracting a blurred version of the image from the original image, thus enhancing the edges and increasing the sharpness of the image.

Conclusion

In conclusion, we have seen how to unblur an image using OpenCV in Python. By applying a Gaussian blur and then an unsharp mask, we can enhance the edges and increase the sharpness of an image. This technique can be useful in various applications such as image restoration, deblurring, and visual enhancement.