JOURNAL ARTICLE

Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm

Qizhi LiuYangen HuangSatoshi GotoTakeshi Ikenaga

Year: 2008 Journal:   IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences Vol: E91-A (8)Pages: 1935-1943   Publisher: Institute of Electronics, Information and Communication Engineers

Abstract

Compared with previous standards, H. 264/AVC adopts variable block size motion estimation (VBSME) and multiple reference frames (MRF) to improve the video quality. Full search motion estimation algorithm (FS), which calculates every search candidate in the search window for 7 block type with multiple reference frames, consumes massive computation power. Mathematical analysis reveals that the aliasing problem of subsampling algorithm comes from high frequency signal components. Moreover, high frequency signal components are also the main issues that make MRF algorithm essential. As we know, a picture being rich of texture must contain lots of high frequency signals. So based on these mathematical investigations, two fast VBSME algorithms are proposed in this paper, namely edge block detection based subsampling method and motion vector based MRF early termination algorithm. Experiments show that strong correlation exists among the motion vectors of those blocks belonging to the same macroblock. Through exploiting this feature, a dynamically adjustment of the search ranges of integer motion estimation is proposed in this paper. Combing our proposed algorithms with UMHS almost saves 96-98% Integer Motion Estimation (IME) time compared to the exhaustive search algorithm. The induced coding quality loss is less than 0.8% bitrate increase or 0.04dB PSNR decline on average.

Keywords:
Motion estimation Motion vector Macroblock Algorithm Block (permutation group theory) Computer science Quarter-pixel motion Aliasing Search algorithm Block-matching algorithm Artificial intelligence Mathematics Computer vision Decoding methods Video processing Image (mathematics) Filter (signal processing) Video tracking

Metrics

3
Cited By
1.01
FWCI (Field Weighted Citation Impact)
13
Refs
0.78
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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