A Gaussian blur kernel is a fundamental tool in image processing and computer vision, used to reduce noise and detail in an image, creating a smooth, blurred effect.
This kernel is derived from the Gaussian function, characterized by its bell-shaped curve, which ensures that pixels closer to the center of the kernel have higher weights and contribute more significantly to the average.
When applying a Gaussian blur, each pixel in the image is replaced by a weighted average of its neighbors, with the weights determined by the Gaussian function. This results in a gradual transition between colors, effectively softening edges and reducing noise without introducing significant artifacts.
The size of the kernel and the standard deviation of the Gaussian function can be adjusted to control the extent of the blurring effect.
C: @3blue1brown
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