Enhancing the Performance of H.264/AVC in Adaptive Group of Pictures Mode Using Octagon and Square Search Pattern
This paper integrates Octagon and Square Search
pattern (OCTSS) motion estimation algorithm into H.264/AVC
(Advanced Video Coding) video codec in Adaptive Group of Pictures
(AGOP) mode. AGOP structure is computed based on scene change
in the video sequence. Octagon and square search pattern block-based
motion estimation method is implemented in inter-prediction process
of H.264/AVC. Both these methods reduce bit rate and computational
complexity while maintaining the quality of the video sequence
respectively. Experiments are conducted for different types of video
sequence. The results substantially proved that the bit rate,
computation time and PSNR gain achieved by the proposed method
is better than the existing H.264/AVC with fixed GOP and AGOP.
With a marginal gain in quality of 0.28dB and average gain in bitrate
of 132.87kbps, the proposed method reduces the average computation
time by 27.31 minutes when compared to the existing state-of-art
H.264/AVC video codec.
[1] Nam Ling, “Expectations and Challenges for Next Generation Video
Compression”, 5th IEEE Conf. on Industrial Electronics and
Applications, pp. 2339-2344, 2010.
[2] Wiegand, T., Sullivan, G. J., Bjontegard, G., et al., “Overview of the
H.264/AVC video coding standard”, IEEE Trans. on CSVT, vol. 13, no.
7, pp. 560-576, 2003.
[3] Sullivan, G. and Wiegand, T., “Video compression - from concepts to
the H.264/AVC standard”, Proc. of the IEEE, vol. 93, pp. 18-31, 2005.
[4] Jungwoo Lee et al., “Rate-Distortion Optimized Frame Type Selection
for MPEG Encoding”, IEEE Transactions on Circuits and Systems for
Video Technology, vol. 7, no. 3, 1997.
[5] Jiro Katto, “Mathematical analysis of MPEG compression capability and
its application to rate control”, Int. Conf. of Image Processing-95, vol.
11, pp. 555-558, 1995.
[6] Sowmyayani, S, Arockia Jansi Rani, P., “Adaptive GOP structure to
H.264/AVC based on Scene change”, ICTACT journal on image and
video processing: special issue on video processing for multimedia
systems, vol. 5, no. 1, pp. 868-872, 2014.
[7] Shilpa Metkar, Sanjay Talbar, “Motion Estimation Techniques for
Digital Video Coding” Springer Briefs in Applied Sciences and
Technology, Computational Intelligence, 2013
[8] Lin, Y. C. Tai, S. C., “Fast full-search block-matching algorithm for
motion-compensated video compression”, IEEE Trans. Communication,
vol. 45, no. 5, pp. 527–531, 1997.
[9] Jong-Nam Kim and Tae-Sun Choi, “A Fast Three Step Search
Algorithm with Minimum Checking Points”, Proc. of IEEE conf. on
Consumer Electronics, vol. 2, no. 4, pp.132-133, 1998.
[10] Li, R., Zeng, B., Liou, M. L., “A new three step search algorithm for
block motion estimation”, IEEE Trans. Circuits Syst. Video Technol.,
vol.4, no.4, pp. 438–442, 1994.
[11] Jianhua Lu, Ming L. Liou, “A Simple and Efficient Search Algorithm
for Block-Matching Motion Estimation”, IEEE Trans. Circuits And
Systems For Video Technology, vol. 7, no. 2, pp. 429-433, 1997.
[12] Po, L.M., Ma, W.C., “A novel four-step search algorithm for fast block
motion estimation”, IEEE Trans. Circuits Syst. Video Technol., vol. 6,
no. 3, pp. 313–317, 1996.
[13] Ghanbari, M., “The Cross-Search Algorithm for Motion Estimation”,
IEEE Trans. on Communications, vol. 38, no. 1, pp. 950-953, 1990.
[14] Zhu, S., Ma, K. K., “A new diamond search algorithm for fast block
matching motion estimation”, IEEE Transactions on Image Processing,
vol. 9, pp. 287–290, 2000.
[15] Zhu, C., Lin, X., Chau, L. P., “Hexagon-based search pattern for fast
block motion estimation”, IEEE Trans. Circuits Syst. Video Technol.,
vol. 12, no. 5, pp. 349–355, 2002.
[16] Faizul Haldi Jamil, Ali Chekima, Rosalyn R, et al., “BMA Performance
of video coding for motion estimation”, IEEE Trans. Int. Conf. on
intelligent system modelling and simulation, 2012.
[17] Cheung, C. H., Po, L. M., “A novel cross-diamond search algorithm for
fast block motion estimation”, IEEE Trans. on Circuits and Systems for
Video Technology, vol. 12, pp. 1168–1177, 2002.
[18] Kamel Belloulata, Shiping Zhu, Zaikuo Wang, “A Fast Fractal Video
Coding Algorithm Using Cross-Hexagon Search for Block Motion
Estimation”, Int. Scholarly Research Network.
[19] Bei-li Zou, Cao Shi, Can-Hui Xu, et al., “Enhanced Hexagonal-Based
Search Using Direction-Oriented Inner Search tor Motion Estimation”,
IEEE Trans. on circuits and systems for video technology, vol. 20, no. 1,
2010.
[20] Cheung, C. H., Po, L. M., “Novel cross-diamond-hexagonal search
algorithms for fast block motion estimation”, IEEE Trans. Multimedia,
vol. 5, no. 1, pp. 16–22, 2005.
[21] Chau, L. P., Zhu, C., “A fast octagon –based search algorithm for
motion estimation”, J. Signal Process, pp. 671–675, 2003.
[22] Chunjiang Duanmu, Yu Zhang, “A New Fast Block Motion Algorithm
Based on Octagon and Triangle Search Patterns for H.264/AVC”, Int.
Journal of Digital Content Technology and its Applications, vol. 6,
no.10, 2012.
[23] Sangeeta Mishra, S., Chittaranjan Pradhan, Alka Singh, “Comparative
Study of Motion Estimation Techniques in Video”, Int. Journal of
Computer Science and Information Technologies, vol. 5, no. 3, pp.
2982-2989, 2014.
[24] Sowmyayani, S., Arockia Jansi Rani, P., “Block based Motion
Estimation using Octagon and Square Pattern”, Int. Journal of Signal
Processing, Image Processing and Pattern Recognition, vol. 7, no. 4, pp.
317-324, 2014.
[25] Lenka Krulikovsk´a and Jaroslav Polec, “GOP Structure Adaptable to
the Location of Shotcuts”, Int. Journal of Electronics and
Telecommunications, vol. 58, no. 2, pp. 129-134, 2012.
[26] Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC
JTC1/SC29/WG11 and ITU-T SG16 Q.6) “H.264/14496-10 AVC
Reference Software Manual (revised for JM 19.0)”, June 2015.
[27] Lenka Krulikovska, Jaroslav Polec, and Michal Martinovic, “Adaptive
Group of Pictures Structure Based On the Positions of Video Cuts”
World Academy of Science, Engineering and Technology International
Journal of Computer, Information Science and Engineering, vol. 7, no.
7, 2013.
[28] Zatt, B., Porto, M., Scharcanski, J., et al., “Gop structure adaptive to the
video content for efficient H.264/AVC encoding”, Proc. of 2010 IEEE
17th International Conference on Image Processing, pp.3053-3056,
2010.
[1] Nam Ling, “Expectations and Challenges for Next Generation Video
Compression”, 5th IEEE Conf. on Industrial Electronics and
Applications, pp. 2339-2344, 2010.
[2] Wiegand, T., Sullivan, G. J., Bjontegard, G., et al., “Overview of the
H.264/AVC video coding standard”, IEEE Trans. on CSVT, vol. 13, no.
7, pp. 560-576, 2003.
[3] Sullivan, G. and Wiegand, T., “Video compression - from concepts to
the H.264/AVC standard”, Proc. of the IEEE, vol. 93, pp. 18-31, 2005.
[4] Jungwoo Lee et al., “Rate-Distortion Optimized Frame Type Selection
for MPEG Encoding”, IEEE Transactions on Circuits and Systems for
Video Technology, vol. 7, no. 3, 1997.
[5] Jiro Katto, “Mathematical analysis of MPEG compression capability and
its application to rate control”, Int. Conf. of Image Processing-95, vol.
11, pp. 555-558, 1995.
[6] Sowmyayani, S, Arockia Jansi Rani, P., “Adaptive GOP structure to
H.264/AVC based on Scene change”, ICTACT journal on image and
video processing: special issue on video processing for multimedia
systems, vol. 5, no. 1, pp. 868-872, 2014.
[7] Shilpa Metkar, Sanjay Talbar, “Motion Estimation Techniques for
Digital Video Coding” Springer Briefs in Applied Sciences and
Technology, Computational Intelligence, 2013
[8] Lin, Y. C. Tai, S. C., “Fast full-search block-matching algorithm for
motion-compensated video compression”, IEEE Trans. Communication,
vol. 45, no. 5, pp. 527–531, 1997.
[9] Jong-Nam Kim and Tae-Sun Choi, “A Fast Three Step Search
Algorithm with Minimum Checking Points”, Proc. of IEEE conf. on
Consumer Electronics, vol. 2, no. 4, pp.132-133, 1998.
[10] Li, R., Zeng, B., Liou, M. L., “A new three step search algorithm for
block motion estimation”, IEEE Trans. Circuits Syst. Video Technol.,
vol.4, no.4, pp. 438–442, 1994.
[11] Jianhua Lu, Ming L. Liou, “A Simple and Efficient Search Algorithm
for Block-Matching Motion Estimation”, IEEE Trans. Circuits And
Systems For Video Technology, vol. 7, no. 2, pp. 429-433, 1997.
[12] Po, L.M., Ma, W.C., “A novel four-step search algorithm for fast block
motion estimation”, IEEE Trans. Circuits Syst. Video Technol., vol. 6,
no. 3, pp. 313–317, 1996.
[13] Ghanbari, M., “The Cross-Search Algorithm for Motion Estimation”,
IEEE Trans. on Communications, vol. 38, no. 1, pp. 950-953, 1990.
[14] Zhu, S., Ma, K. K., “A new diamond search algorithm for fast block
matching motion estimation”, IEEE Transactions on Image Processing,
vol. 9, pp. 287–290, 2000.
[15] Zhu, C., Lin, X., Chau, L. P., “Hexagon-based search pattern for fast
block motion estimation”, IEEE Trans. Circuits Syst. Video Technol.,
vol. 12, no. 5, pp. 349–355, 2002.
[16] Faizul Haldi Jamil, Ali Chekima, Rosalyn R, et al., “BMA Performance
of video coding for motion estimation”, IEEE Trans. Int. Conf. on
intelligent system modelling and simulation, 2012.
[17] Cheung, C. H., Po, L. M., “A novel cross-diamond search algorithm for
fast block motion estimation”, IEEE Trans. on Circuits and Systems for
Video Technology, vol. 12, pp. 1168–1177, 2002.
[18] Kamel Belloulata, Shiping Zhu, Zaikuo Wang, “A Fast Fractal Video
Coding Algorithm Using Cross-Hexagon Search for Block Motion
Estimation”, Int. Scholarly Research Network.
[19] Bei-li Zou, Cao Shi, Can-Hui Xu, et al., “Enhanced Hexagonal-Based
Search Using Direction-Oriented Inner Search tor Motion Estimation”,
IEEE Trans. on circuits and systems for video technology, vol. 20, no. 1,
2010.
[20] Cheung, C. H., Po, L. M., “Novel cross-diamond-hexagonal search
algorithms for fast block motion estimation”, IEEE Trans. Multimedia,
vol. 5, no. 1, pp. 16–22, 2005.
[21] Chau, L. P., Zhu, C., “A fast octagon –based search algorithm for
motion estimation”, J. Signal Process, pp. 671–675, 2003.
[22] Chunjiang Duanmu, Yu Zhang, “A New Fast Block Motion Algorithm
Based on Octagon and Triangle Search Patterns for H.264/AVC”, Int.
Journal of Digital Content Technology and its Applications, vol. 6,
no.10, 2012.
[23] Sangeeta Mishra, S., Chittaranjan Pradhan, Alka Singh, “Comparative
Study of Motion Estimation Techniques in Video”, Int. Journal of
Computer Science and Information Technologies, vol. 5, no. 3, pp.
2982-2989, 2014.
[24] Sowmyayani, S., Arockia Jansi Rani, P., “Block based Motion
Estimation using Octagon and Square Pattern”, Int. Journal of Signal
Processing, Image Processing and Pattern Recognition, vol. 7, no. 4, pp.
317-324, 2014.
[25] Lenka Krulikovsk´a and Jaroslav Polec, “GOP Structure Adaptable to
the Location of Shotcuts”, Int. Journal of Electronics and
Telecommunications, vol. 58, no. 2, pp. 129-134, 2012.
[26] Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC
JTC1/SC29/WG11 and ITU-T SG16 Q.6) “H.264/14496-10 AVC
Reference Software Manual (revised for JM 19.0)”, June 2015.
[27] Lenka Krulikovska, Jaroslav Polec, and Michal Martinovic, “Adaptive
Group of Pictures Structure Based On the Positions of Video Cuts”
World Academy of Science, Engineering and Technology International
Journal of Computer, Information Science and Engineering, vol. 7, no.
7, 2013.
[28] Zatt, B., Porto, M., Scharcanski, J., et al., “Gop structure adaptive to the
video content for efficient H.264/AVC encoding”, Proc. of 2010 IEEE
17th International Conference on Image Processing, pp.3053-3056,
2010.
@article{"International Journal of Electrical, Electronic and Communication Sciences:71221", author = "S. Sowmyayani and P. Arockia Jansi Rani", title = "Enhancing the Performance of H.264/AVC in Adaptive Group of Pictures Mode Using Octagon and Square Search Pattern", abstract = "This paper integrates Octagon and Square Search
pattern (OCTSS) motion estimation algorithm into H.264/AVC
(Advanced Video Coding) video codec in Adaptive Group of Pictures
(AGOP) mode. AGOP structure is computed based on scene change
in the video sequence. Octagon and square search pattern block-based
motion estimation method is implemented in inter-prediction process
of H.264/AVC. Both these methods reduce bit rate and computational
complexity while maintaining the quality of the video sequence
respectively. Experiments are conducted for different types of video
sequence. The results substantially proved that the bit rate,
computation time and PSNR gain achieved by the proposed method
is better than the existing H.264/AVC with fixed GOP and AGOP.
With a marginal gain in quality of 0.28dB and average gain in bitrate
of 132.87kbps, the proposed method reduces the average computation
time by 27.31 minutes when compared to the existing state-of-art
H.264/AVC video codec.", keywords = "Block Distortion Measure, Block Matching
Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot
cut detection.", volume = "9", number = "8", pages = "980-5", }
