Another way to approach dithering is to analyse the input image in order to make informed decisions about how best to perturb pixel values prior to quantisation. Error-diffusion dithering does this by sequentially taking the quantisation error for the current pixel (the difference between the input value and the quantised value) and distributing it to surrounding pixels in variable proportions according to a diffusion kernel . The result is that input pixel values are perturbed just enough to compensate for the error introduced by previous pixels.
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In this episode, James Gallagher speaks to Dr Chris Ponting about the latest DecodeME results, which point to a strong genetic component to ME. And Professor Rosemary Boyton outlines the ambition behind the new Rosetta Stone study, designed to build a detailed evidence base of shared biomarkers across ME and Long COVID.