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Currently, when passed an input image of eltype Colorant{T}, the dithered output image is computed using the floating point number type T provided by the user.
Since the goal of dithering is image quantization, it would be reasonable to exclusively use quantized N0f8 fixed-point numbers from FixedPointNumbers.jl internally.
This would also enable the optional use of a look-up table of closest colors. Currently, the performance bottleneck of most dithering algorithms is a large amount of calls to colordiff from Colors.jl. For color palettes of size $n$, this function is called at least $n$ times on each pixel. For an upfront cost of $256^3 \cdot n$ calls to colordiff, a N0f8 look-up table could be computed instead. This would open up DitherPunk for dithering of live-video.
The text was updated successfully, but these errors were encountered:
Addresses #70.
Currently, when passed an input image of eltype
Colorant{T}
, the dithered output image is computed using the floating point number typeT
provided by the user.Since the goal of dithering is image quantization, it would be reasonable to exclusively use quantized
N0f8
fixed-point numbers from FixedPointNumbers.jl internally.This would also enable the optional use of a look-up table of closest colors. Currently, the performance bottleneck of most dithering algorithms is a large amount of calls to$n$ , this function is called at least $n$ times on each pixel. For an upfront cost of $256^3 \cdot n$ calls to
colordiff
from Colors.jl. For color palettes of sizecolordiff
, aN0f8
look-up table could be computed instead. This would open up DitherPunk for dithering of live-video.The text was updated successfully, but these errors were encountered: