Low Computational Complexity Variable Block Size (VBS) Partitioning for Motion Estimation Using the Walsh Hadamard Transform (WHT)

Variable Block Size (VBS) based motion estimation has been adapted in state of the art video coding, such asH.264/AVC, VC-1. However, a low complexity H.264/AVCencoder cannot take advantage of VBS due to its power consumption requirements. In this paper, we present a VBS partition algorithm based on a binary motion edge map without either initial motion estimation or Rate-Distortion (R-D)optimization for selecting modes. The proposed algorithm uses the Walsh Hadamard Transform (WHT) to create a binary edge map, which provides a computational complexity cost effectiveness compared to other light segmentation methods typically used to detect the required region.

[1]  Satoshi Goto,et al.  Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm , 2008, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[2]  Shang-Hong Lai,et al.  Efficient NCC-Based Image Matching in Walsh-Hadamard Domain , 2008, ECCV.

[3]  André Kaup,et al.  Laplace Distribution Based Lagrangian Rate Distortion Optimization for Hybrid Video Coding , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[4]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Yacov Hel-Or,et al.  Real-time pattern matching using projection kernels , 2003, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Wen Gao,et al.  Laplacian Distortion Model (LDM) for Rate Control in Video Coding , 2007, PCM.

[7]  Shoulie Xie,et al.  Unified complex Hadamard transform sequences for multi-carrier CDMA systems , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[8]  Henrique S. Malvar,et al.  Low-complexity transform and quantization in H.264/AVC , 2003, IEEE Trans. Circuits Syst. Video Technol..

[9]  Jean-Luc Nagel,et al.  A low-complexity video coder based on the Discrete Walsh Hadamard Transform , 2000, 2000 10th European Signal Processing Conference.

[10]  Lawrence A. Rowe,et al.  Laplacian Model For Ac Dct Terms In Image And Video Coding , 1996 .

[11]  M. N. Shanmukha Swamy,et al.  Discrete tchebichef transform-A fast 4x4 algorithm and its application in image/video compression , 2008, 2008 IEEE International Symposium on Circuits and Systems.

[12]  Ramakrishnan Mukundan,et al.  A Comparison of Discrete Orthogonal Basis Functions for Image Compression , 2004 .

[13]  Gunilla Goulding,et al.  Time Series Analyzer , 2002 .

[14]  Nasir M. Rajpoot Simulation of the rate-distortion behaviour of a memoryless Laplacian source , 2002 .

[15]  Lauri Koskinen,et al.  CNN-type algorithms for H.264 variable block-size partitioning , 2007, Signal Process. Image Commun..