Convolution Kernel: Difference between revisions
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[[Category:Techniques]] | [[Category:Techniques]] | ||
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= | |||
==Edge Detection== | ==Edge Detection== | ||
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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. | 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 | Unsharp masks have been a very popular choice in [[tennis]] in the late 2010's, popularized by players like {{mafar}}. | ||