IEICE TRANSACTIONS on Fundamentals
Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm
Summary :
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 0.04 dB PSNR decline on average.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.8 pp.1935-1943
- Publication Date
- 2008/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.8.1935
- Type of Manuscript
- Special Section PAPER (Special Section on Signal Processing)
- Category
Authors
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Qin LIU, Yiqing HUANG, Satoshi GOTO, Takeshi IKENAGA, "Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 8, pp. 1935-1943, August 2008, doi: 10.1093/ietfec/e91-a.8.1935.
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 0.04 dB PSNR decline on average.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.8.1935/_p
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@ARTICLE{e91-a_8_1935,
author={Qin LIU, Yiqing HUANG, Satoshi GOTO, Takeshi IKENAGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm},
year={2008},
volume={E91-A},
number={8},
pages={1935-1943},
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 0.04 dB PSNR decline on average.},
keywords={},
doi={10.1093/ietfec/e91-a.8.1935},
ISSN={1745-1337},
month={August},}
Copy
TY - JOUR
TI - Edge Block Detection and Motion Vector Information Based Fast VBSME Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1935
EP - 1943
AU - Qin LIU
AU - Yiqing HUANG
AU - Satoshi GOTO
AU - Takeshi IKENAGA
PY - 2008
DO - 10.1093/ietfec/e91-a.8.1935
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2008
AB - 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 0.04 dB PSNR decline on average.
ER -
English
