This is an ImageMagick script that does the following:

1. Downscale the image
2. Run the Kuwahara filter
3. Use ordered dithering with 8 colors
4. Interpolate pixels using the nearest neighbor algorithm with a Box filter
5. Upscale back to the original size

Usage

Requirements:

• python3
• ImageMagick

./kuw_dither.py $INPUT_FILE_NAME

Inspiration

4Chan /wg

I found a post on 4chan's /wg board awhile back that had some interesting edits. The link to the original thread is now dead, but the original post was:

I was fucking around and found a fun way of livening up old and/or low res wallpapers, and I'll be dumping some and sharing the technique. To my knowledge this will require photoshop.

>open your image in PS
>shrink it to exactly half or a quarter of your screen's resolution
>gaussian blur if desired
>save for web as PNG-8 using "Restrictive" color reduction and "Pattern" dithering, setting colors to "Auto" or your desired bit depth
>close, and open your newly exported file
>upscale the image to full res using "Nearest Neighbor" in resampling
>win

Low Tech Magazine

I found a post on Low Tech Magazine that discussed how they redesigned their blog to be more energy efficient. One of the things they did was dither all images to reduce image size.

Acerola: The Kuwahara Filter

More recently, I watched a video called 'The Kuwahara Filter' by Acerola. In the video, he explains how the Kuwahara filter was created and potential use cases. One interesting combination he mentions is using the Kuwahara filter and then dithering.

Seph's Blog

On Seph, Joseph Gentle's blog, his tiled background image looks like some sort of dithered pixelated pattern.

All Together

From these sources, I decided that I'd try to emulate the recipe from the 4Chan post but with Kuwahara filter rather than a Gaussian blur. I don't know how to use PhotoShop so I'm opting to use ImageMagick instead. I also get the added benefit of creating a simple program instead of having to go through PhotoShop GUI flows in the future.

I want to create a general filter that looks cool. I'll then use the filter to create a similar background image to Seph's blog for my own website.

Experimentation

After readint the Low Tech Magazine article, I experimented with just dithering with ImageMagick. This went okay but I wasn't able to get an effect I liked.

After going through all the above inspiration, I started off experimenting with different levels of Kuwahara filtering with different dithering algorithms. The outputs of the Floyd-Steinberg and Riemersma filters produced interesting images but they weren't as geometric as my original 4Chan inspiration.

Result

Finally, I figured out that using ordered dithering, I could achieve what I was looking for. After some experimentation, I settled on using ordered dithering with ordered 8x8 threshold map at level 3. The final ImageMagick script is:

convert $INPUT \
    \( -resize 50% )\
    \( -kuwahara 1 \) \
    \( -ordered-dither o8x8,3 -colors 8 \) \
    \( -interpolate Nearest -filter Box \) \
    \( -resize 200% \) \
    $OUTPUT

To summarize:

1. Downscale the image
2. Run the Kuwahara filter
3. Use ordered dithering with 8 colors
4. Interpolate pixels using the nearest neighbor algorithm with a Box filter
5. Upscale back to the original size

Tweaking Parameters

Downscale

Tweaking the initial downscale will result in a more obvious filter. When the Kuwahara filter and dithering effect have fewer pixels to work with, their effects are more pronounced.

Kuwahara Filter

Increasing the Kuwahara filter radius will give a more painter like look to the final image. More areas of color will get splotched together.

Dithering

Different dithering algorithms will produce different effects. Using the Floyd-Steinberg algorithm will produce a much less pixelated look. With Ordered dithering, I was able to produce a much more grid like pixelated look.

Having 8 colors usually produces an image that looks distinctly filtered. With 16 or 32 colors, I usually will get enough colors that output will still look fairly close to the input in terms of color.

Interpolation

Interpolation will give the final result a more pixelated look. Using the Box or Point filters gives a harsher look while the Triangle filter results in a softer image.

Upscale

The final upscale is just to get the image back to it's original size. I use the inverse of the downscale percentage to do this.