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Smoothing | Fundamentals of Image Manipulation with Python
Fundamentals of Image Manipulation with Python
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Course Content

Fundamentals of Image Manipulation with Python

bookSmoothing

In OpenCV, Gaussian Blur is a smoothing filter used to reduce noise and detail in an image. This filter is based on the Gaussian function, which is bell-shaped and diminishes as the distance from the center increases. The cv2.GaussianBlur() function applies this type of blur to an image.

The function requires three parameters:

  • the image to be blurred;
  • the kernel size (specified as a tuple of width and height);
  • the standard deviation in the x and y directions.

If the standard deviation is set to zero, it is calculated from the kernel size. The kernel size determines the area used to calculate the blur, while the standard deviation controls the amount of blur.

Task
test

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  1. Apply Gaussian blue to the image "image1.jpg".

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In OpenCV, Gaussian Blur is a smoothing filter used to reduce noise and detail in an image. This filter is based on the Gaussian function, which is bell-shaped and diminishes as the distance from the center increases. The cv2.GaussianBlur() function applies this type of blur to an image.

The function requires three parameters:

  • the image to be blurred;
  • the kernel size (specified as a tuple of width and height);
  • the standard deviation in the x and y directions.

If the standard deviation is set to zero, it is calculated from the kernel size. The kernel size determines the area used to calculate the blur, while the standard deviation controls the amount of blur.

Task
test

Swipe to show code editor

  1. Apply Gaussian blue to the image "image1.jpg".

Mark tasks as Completed
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 1. Chapter 7
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