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The top row shows the full image, whereas close-ups are displayed on the other rows. A clean 465 × 348 image (original author: Heinz Albers, source: wikipedia) was corrupted by a Gaussian additive white noise with standard deviation ? = 10, then denoised with the ROF, TV-LSE and TV-ICE algorithms. The parameters were chosen so that the norm of the estimated noisê u ? u was the same for each algorithm, leading to: ? = 20, ? = 10 for TV-LSE (initial choice, TV-ICE, and ? = 15.6 for ROF. Note the similarity between LSE and ICE, and the staircasing effect clearly visible on the ROF close-ups ,
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