"Retaining the flow of used petrol and diesel vehicles into the island will help enable a more just transition for islanders, ensuring the burden of change does not unnecessarily impact on those worst off".
Due to this more measured approach, error-diffusion dithering is even better at preserving details and can produce a more organic looking final image. However, the algorithm itself is inherently serial and not easily parallelised. Additionally, the propagation of error can cause small discrepancies in one part of the image to cascade into other distant areas. This is very obvious during animation, where pixels will appear to jitter between frames. It also makes files harder to compress.
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As you might expect, the result of this is that colours which lie closer to the input pixel are given a greater proportion of the total influence with ever-increasing values of . This is not mentioned in the cited paper but it might be nice to consider for your own implementation.
The problem is compounded by APIs that implicitly create stream branches. Request.clone() and Response.clone() perform implicit tee() operations on the body stream — a detail that's easy to miss. Code that clones a request for logging or retry logic may unknowingly create branched streams that need independent consumption, multiplying the resource management burden.