The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:
It got under way in 2022 and its final report is not expected until 2027. It has already cost £192m – a figure which is expected to rise past £200m by the time it is finished, making it one of the most expensive public inquiries in history.
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