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Two-dimensional Non-separable Adaptive Wiener Interpolation Filter for H.264/AVC

Two-dimensional Non-separable Adaptive Wiener Interpolation Filter for H.264/AVC. Yuri Vatis Institut für Informationsverarbeitung, Universität Hannover ITG-FA 3.2, 23.06.2005. Outline. Introduction Motion Compensated Prediction Adaptive Interpolation Filter Experimental Results

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Two-dimensional Non-separable Adaptive Wiener Interpolation Filter for H.264/AVC

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  1. Two-dimensional Non-separable Adaptive Wiener Interpolation Filter for H.264/AVC Yuri Vatis Institut für Informationsverarbeitung, Universität Hannover ITG-FA 3.2, 23.06.2005

  2. Outline • Introduction • Motion Compensated Prediction • Adaptive Interpolation Filter • Experimental Results • Conclusion

  3. Introduction S S Hybrid Video Encoder: Video input Bitstream s(t) e(t) + Quant EC T - T-1 + + MCP z -1 d(t) s’(t-1) ME

  4. Motion Compensated Prediction (MCP) d(t) s‘(t-1) s(t) reference block block to code

  5. Motion Compensated Prediction (MCP) MCP with fractional-pel Motion Vector Resolution i Prediction is distorted by: 1. Aliasing in s(t) and s’(t-1) 2. Displacement estimation errors of d(t) 3. Quantisation errors in s’(t-1) 4. etc.  The distortions depend on the motion and content of the video signal j d(t) s’(t-1) s(t) reference block block to code  image signal on sub-pel positions has to be generated by interpolation

  6. 2D non-separable Adaptive Interpolation Filter • Analytical design of a non-separable adaptive 2D interpolation filter. • Goal: • Prediction (and not just interpolation) of picture elements by minimising prediction error energy. • Reduction of aliasing and blurring effects, motion estimation errors. • Properties: • Symmetric, non-separable 6x6-tap filter. • Filter coefficients are calculated analytically once per frame with respect to all reference frames.

  7. Adaptive Interpolation Filter • Value ( ) to be interpolated: where is an integer sample value ( ) and are filter coefficients for sub-pel position SP

  8. Analytical Calculation of Filter Coefficients The calculation of coefficients and the motion compensation are performed in the following 3 steps: • Displacement vectors are estimated for every image to be coded (standard interpolation filter is used). • Independent calculation of 2D filter coefficients for each sub-pel position by minimisation of the prediction error energy: with

  9. Analytical Calculation of Filter Coefficients • Estimation of new displacement vectors (applying the adaptive interpolation filter computed in 2). • Reducing motion estimation errors, caused by aliasing, camera noise etc. • Treating the problem in the rate-distortion sense. • The software was declared as a VCEG KTA-Software

  10. Quantisation and Coding of Filter Coefficients • Quantisation with 8 bits (magnitude). • Required side information for filter coefficients @30 fps ( [VCIP05] ):

  11. CIF ( HDTV) Results ProfileIDC 100 QPISlice 23, 27, 31, 35 IntraPeriod 0 QPPSlice 24, 28, 32, 36 NumberBFrames 3 QPBSlice 25, 29, 33, 37 BReferencePictures 1 PyramidCoding 1 PyramidLevelQPEnable 1 SearchRange 32 (64) NumberReferenceFrames 5 (3) SymbolMode 1 AdaptiveRounding 1 Transform8x8 1

  12. Concrete, CIF, 400 Frames @ 30 fps

  13. Crew, HDTV(720p), 20 Frames @ 60 fps

  14. Raven, HDTV(720p), 40 Frames @ 60 fps

  15. Sunflower, HDTV(1080p), 100 Frames @ 25 fps

  16. Conclusions • Average of 12% bit rate savings compared to the standard H.264/AVC • Slightly increased decoder complexity • Number of operations needed for interpolation is increased • Suitable for 24-bit arithmetic

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