Convolution Kernel

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A Convolution Kernel is when you use specific matrix transformations (known as convolutions) into a image's kernel to create a wide variety of effects. Working with these kernels can create a wide variety of effects, from blurs to sharpens and more.

While many effects in modern editors stem from a convolution kernel they usually limit editing to just that one style of effect; working with convolution kernels directly is rare as it often requires a linear algebra background and the manual editing of many matrix points.

Effect Types

Emboss

One of the most well known and instantly recognizable convolution patterns, instantly recognizable from its gray coloring and black outlines. Available as a preset in almost every major editor, including Premiere, Vegas and Kdenlive.

Edge Detection

Another well known filter that emphasizes the "edges" of an image and removes almost everything else.

Sharpen

Similar to edge detection, sharpen will emphasize edges - without removing other details.

Gaussian Blur

A special type of Blur based on the Gaussian function.

Unsharp Mask

An unsharp mask is a type of convolution kernel where the image is masked with a copy that is blurred (or "un-sharpened"). This can make a clearer image that may have less detail.

Unsharp masks have been a very popular choice in tennis in the late 2010's, popularized by players like mafar_.