I am trying to reduce aliasing in an image using some filters. I tried the Gaussian variant of filters to remove the said high frequency patterns in the image, but I feel it's a bit too much of a blur.

I need a filter that can help me do some kind of anti-aliasing without doing too much blur.

I have searched a lot and unfortunately the results are not fruitful.

  • $\begingroup$ What are you requirements? Gaussian kernels are designed to blur without artifacts. A different kernel that blurs but isn't Gaussian is the box filter. It will produce artifacts however. I suppose more importantly, why isn't Gaussian good enough? $\endgroup$ Commented Jul 10, 2017 at 20:26
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    $\begingroup$ What kind of aliasing is present? Is it a synthetic image with staircasing/jaggies? Is it a texture with spurious low-frequency components (like a high-frequency grating or checkerboard)? Is it a photo that's been badly upscaled? $\endgroup$
    – Dan Hulme
    Commented Jul 11, 2017 at 11:07
  • $\begingroup$ The image consist of Jaggies mostly ... like for instance, i have an image filled with Grass and I want to make sure that the grass blades are not too blurred. $\endgroup$ Commented Jul 11, 2017 at 11:22
  • $\begingroup$ a sinc filter can downsample "perfectly" such that any details that would cause aliasing are removed, while other details are left perfectly alone. en.wikipedia.org/wiki/Sinc_filter $\endgroup$
    – Alan Wolfe
    Commented Jul 15, 2017 at 0:34

1 Answer 1


Depending on the specific content of your input images, you could either use the Gaussian filter with kernel size varying with distance from the camera ( Link ) or use a slightly more complex bilateral filter, which is widely used to eliminate noise while keeping edges mostly intact.


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