Knowing this, we can modify the N-Convex algorithm covered earlier such that the candidate weights are given by the barycentric coordinates of the input pixel after being projected onto a triangle whose vertices are given by three surrounding colours, abandoning the IDW method altogether1. This results in a fast and exact minimisation of , with the final dither being closer in quality to that of Knoll’s Algorithm.
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Data flows left to right. Each stage reads input, does its work, writes output. There's no pipe reader to acquire, no controller lock to manage. If a downstream stage is slow, upstream stages naturally slow down as well. Backpressure is implicit in the model, not a separate mechanism to learn (or ignore).
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