Ordered Dithering with Arbitrary or Irregular Colour Palettes (2023)
9 hours ago
- #image-processing
- #color-quantisation
- #dithering
- Introduction to dithering in image processing, focusing on color reduction and quantisation.
- Comparison of dithering with and without random perturbation, highlighting the simulation of smooth transitions.
- Ordered Dithering explained, using a threshold map for structured perturbations to preserve detail.
- Error-Diffusion Dithering introduced, detailing its sequential error distribution for organic-looking results.
- Challenges of Palette Quantisation with arbitrary color palettes and the effectiveness of error-diffusion.
- Distinction between Regular and Irregular Palettes and modifications for ordered dithering.
- The Probability Matrix approach for palette dithering, treating the threshold matrix as a probability matrix.
- N-Closest Algorithm described, using inverse distance weighting for candidate color selection.
- N-Convex Algorithm outlined, focusing on centroid proximity and error compensation.
- Thomas Knoll’s Algorithm presented, emphasizing exact error minimisation through repeated candidate selection.
- Barycentric Coordinates and Triangulated Irregular Network (TIN) for geometric linear combination solutions.
- Natural Neighbour Interpolation discussed, offering smooth transitions between color samples.
- Joel Yliluoma’s Algorithms introduced, considering perceptual quality in dithering.
- Tetrapal library mentioned for Delaunay triangulation of color palettes for dithering applications.
- Appendixes covering Candidate Sorting, Linear RGB Space, and Threshold Matrices and Noise Functions.