How to Gaussian blur an image using Python

How to use Python to perform Gaussian blur on pictures

Introduction:
Gaussian blur is a commonly used image processing technique that can make images smoother and blur, used to reduce noise or add certain artistic effects. In this article, we will use Python to write code to implement Gaussian blur on images.

1. Understand the principle of Gaussian blur
   Gaussian blur is based on the Gaussian filter, which achieves the blur effect of the image by calculating the weighted average of the pixels around each pixel. The weight of the weighted average is determined by a Gaussian function, and the farther away from the central pixel, the smaller the weight. The blurring effect is achieved by applying a weighted average to each pixel of the entire image.
2. Import the required libraries
   Before we start writing code, we first need to import the relevant libraries. The libraries used in this article are OpenCV and NumPy.

import cv2
import numpy as np

3. Load the image and set the blur effect parameters
   Next, we need to load the image to be blurred and set the Gaussian blur parameters. Here, we can adjust the blur radius (blur_radius) to control the degree of blur.

image = cv2.imread('image.jpg')
blur_radius = 10

4. Perform Gaussian blur processing
   By calling the GaussianBlur() function in OpenCV, we can perform Gaussian blur processing on the image. The parameters of this function include the original image, blur radius, and standard deviation (used to calculate the weights of the Gaussian function). The returned result is the blurred image.

blurred_image = cv2.GaussianBlur(image, (blur_radius, blur_radius), 0)

5. Save and display the results
   Finally, we save the blurred image locally and display it using OpenCV's imshow() function. You can run the following code to implement this step and see the final result.

cv2.imwrite('blurred_image.jpg', blurred_image)
cv2.imshow('Blurred Image', blurred_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

The complete code is as follows:

import cv2
import numpy as np

# 加载图片和设置模糊效果参数
image = cv2.imread('image.jpg')
blur_radius = 10

# 进行高斯模糊处理
blurred_image = cv2.GaussianBlur(image, (blur_radius, blur_radius), 0)

# 保存并显示结果
cv2.imwrite('blurred_image.jpg', blurred_image)
cv2.imshow('Blurred Image', blurred_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Summary:
By using Python and OpenCV, we can easily achieve the effect of Gaussian blur on images. By adjusting the blur radius, we can freely control the degree of blur. Gaussian blur can not only be used to reduce noise in images, but can also create some beautiful artistic effects. If you're interested in image processing, this is an interesting and practical technique worth checking out.

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