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Artifacts suppression in images and video. Volodymyr Fedak. Introduction. What is the problem? Why is it important? What did I do? What are the results? So what next?. What is the problem?. blocking ringing blurring flickering. What is the problem?. F - 2. F - 1. F. F + 1. F + 2.
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Artifacts suppression in images and video Volodymyr Fedak
Introduction • What is the problem? • Why is it important? • What did I do? • What are the results? • So what next?
What is the problem? • blocking • ringing • blurring • flickering
What is the problem? F - 2 F - 1 F F + 1 F + 2 Intra-frame processing… Inter-frame processing…
Compressed information De-coder Artifact detection Reducing artifacts Transform to original format Enhanced information Coder parameters postprocessing Why is it important ? Postprocessing techniques: • spatial-temporal algorithmsalgorithms that transform signal to frequency domain • motion-compensated algorithmsiterative approaches based on the theory of projections onto convex set
What did I do ? • Analyse modern postprocessing techniques • Implement most encouraging methods • Compare results of mentioned algorithms • Propose approaches for optimization
Wavelet-based de-blocking and de-ringing algorithm proposed by Alan and Liew • Steps: • Detection of Block Discontinuities • Threshold Maps Generation at Different Wavelet Scales • low frequency filtering
Non-Local Means NLM is an improvement of Bilateral filtering C(y, x) - geometric relationship S(I(y), I(x)) - luminance ratio I(y) – pixel luminance
NLM could be presented: in general way: in terms of implementation: v(i) – noisy image W(i, j) - weighted average of pixels in the image v(j) – pixel luminance Non-Local Means N(x) - window surrounding pixel x; Q(x) is a search window around pixel x;
Non-Local Means Parameters • h - determines the amount of averaging (h increases amount of blocking artifacts decrease). • N (x) – the match window/patch – when N(x) increases, blocking artifacts of the processed sequence decreases very slowly • Q(x) – the search window/patch – when Q(x) increases, artifacts of the processed sequence decreases very slowly for an increasing value of the search window size, and we have a large amount of computation time.
Possible ways for optimization: • Extended NLM to the temporal domain . Use together with motion-compensation algorithm but apply some quality coefficient to the motion vector. • Add smart patch/search window size choosing algorithm. • Use Hierarchical block matching algorithm to find similar windows for speeding-up NLM