alt Hacker NewsIt's important to note that the approach described focuses on giving fast results, not the best results.
Simply trying every character and considering their entire bitmap, and keeping the character that reduces the distance to the target gives better results, at the cost of more CPU.
This is a well known problem because early computers with monitors used to only be able to display characters.
At some point we were able to define custom character bitmap, but not enough custom characters to cover the entire screen, so the problem became more complex. Which new character do you create to reproduce an image optimally?
And separately we could choose the foreground/background color of individual characters, which opened up more possibilities.
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You said “best results”, but I imagine that the theoretical “best” may not necessarily be the most aesthetically pleasing in practice.
For example, limiting output to a small set of characters gives it a more uniform look which may be nicer. Then also there’s the “retro” effect of using certain characters over others.
And a (the?) solution is using an algorithm like k-means clustering to find the tileset of size k that can represent a given image the most faithfully. Of course that’s only for a single frame at a time.
In practice isn’t a large HashMap best for lookup, based on compile-time or static constants describing the character-space?
Thinking more about the "best results". Could this not be done by transforming the ascii glyphs into bitmaps, and then using some kind of matrix multiplication or dot production calculation to calculate the ascii character with the highest similarity to the underlying pixel grid? This would presumably lend itself to SIMD or GPU acceleration. I'm not that familiar with this type of image processing so I'm sure someone with more experience can clarify.