Block Adaptive Interpolation Filter Using Trained Dictionary for Sub-Pixel Motion Compensation

Adaptive interpolation filtering for sub-pel motion compensation is one of key techniques of ITU-T key technology area (KTA) codec. However, the adaptive interpolation filtering has a limitation in coding efficiency because of its frame-based update strategy of filter coefficients. Although switched interpolation filter with offset is presented as a sort of block-adaptive filtering for KTA codec, its coding efficiency is generally lower than that of the best adaptive interpolation filter. In order to overcome such a problem, this paper presents an advanced block-adaptive interpolation filtering using well-trained dictionaries which store optimized filter coefficients. We derive those filter coefficients by using learning-based super-resolution. The proposed block-adaptive interpolation filtering for quarter-pel motion compensation consists of two steps: up-scaling of half-pel accuracy and subsequent up-scaling of quarter-pel accuracy. The dictionary optimized for each step is employed to produce the precise up-scaled pixels. Simulation results show that the proposed algorithm improves higher coding efficiency than the previous adaptive interpolation filters for KTA.

[1]  Thomas Wedi,et al.  Separable adaptive interpolation filter for video coding , 2008, 2008 15th IEEE International Conference on Image Processing.

[2]  Byung Cheol Song,et al.  Noise-robust superresolution based on a classified dictionary , 2010, J. Electronic Imaging.

[3]  F. Bossen,et al.  Common test conditions and software reference configurations , 2010 .

[4]  Simon Haykin,et al.  Adaptive filter theory (2nd ed.) , 1991 .

[5]  Jörn Ostermann,et al.  Adaptive Interpolation Filter for H.264/AVC , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  Yu-Wen Huang,et al.  Localized multiple adaptive interpolation filters with single-pass encoding , 2010, Visual Communications and Image Processing.

[7]  Dit-Yan Yeung,et al.  Image Hallucination Using Neighbor Embedding over Visual Primitive Manifolds , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Chang-Hsing Lee,et al.  A fast motion estimation algorithm based on the block sum pyramid , 1997, IEEE Trans. Image Process..

[9]  Moncef Gabbouj,et al.  Video Coding With Low-Complexity Directional Adaptive Interpolation Filters , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  William T. Freeman,et al.  Example-Based Super-Resolution , 2002, IEEE Computer Graphics and Applications.

[11]  G. Bjontegaard,et al.  Calculation of Average PSNR Differences between RD-curves , 2001 .

[12]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[13]  Jörn Ostermann,et al.  Motion-and aliasing-compensated prediction using a two-dimensional non-separable adaptive Wiener interpolation filter , 2005, IEEE International Conference on Image Processing 2005.

[14]  Jörn Ostermann,et al.  Locally Adaptive Non-Separable Interpolation Filter for H.264/AVC , 2006, 2006 International Conference on Image Processing.

[15]  de G Gerard Haan,et al.  Making the best of legacy video on modern displays , 2007 .