artifacts suppression in images and video
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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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Presentation Transcript
  • What is the problem?
  • Why is it important?
  • What did I do?
  • What are the results?
  • So what next?
what is the problem
What is the problem?
  • blocking
  • ringing
  • blurring
  • flickering
what is the problem1
What is the problem?

F - 2

F - 1


F + 1

F + 2

Intra-frame processing…

Inter-frame processing…

why is it important

Compressed information


Artifact detection

Reducing artifacts

Transform to original format



Coder parameters


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
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
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
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

non local means1

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
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
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