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Pattern-based integer sample motion search strategies in the context of HEVC

: Maier, Georg; Bross, B.; Grois, D.; Marpe, D.; Schwarz, H.; Veltkamp, R.C.; Wiegand, T.

Postprint urn:nbn:de:0011-n-3603994 (493 KByte PDF)
MD5 Fingerprint: 40137f3eacb9efc9f8c230cc619d665d
Copyright Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Erstellt am: 29.9.2015

Tescher, Andrew G. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Applications of Digital Image Processing XXXVIII : San Diego, California, United States, August 09, 2015
Bellingham, WA: SPIE, 2015 (Proceedings of SPIE 9599)
ISBN: 978-1-62841-765-4
Paper 95991A, 16 S.
Conference "Applications of Digital Image Processing" <38, 2015, San Diego/Calif.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
Fraunhofer HHI ()
video compression; motion estimation; inter-picture prediction; H.265; MPEG-H; HEVC; integer sample motion search

The H.265/MPEG-H High Efficiency Video Coding (HEVC) standard provides a significant increase in coding efficiency compared to its predecessor, the H.264/MPEG-4 Advanced Video Coding (AVC) standard, which however comes at the cost of a high computational burden for a compliant encoder. Motion estimation (ME), which is a part of the inter-picture prediction process, typically consumes a high amount of computational resources, while significantly increasing the coding efficiency. In spite of the fact that both H.265/MPEG-H HEVC and H.264/MPEG-4 AVC standards allow processing motion information on a fractional sample level, the motion search algorithms based on the integer sample level remain to be an integral part of ME. In this paper, a flexible integer sample ME framework is proposed, thereby allowing to trade off significant reduction of ME computation time versus coding efficiency penalty in terms of bit rate overhead. As a result, through extensive experimentation, an integer sample ME algorithm that provides a good trade-off is derived, incorporating a combination and optimization of known predictive, pattern-based and early termination techniques. The proposed ME framework is implemented on a basis of the HEVC Test Model (HM) reference software, further being compared to the state-of-the-art fast search algorithm, which is a native part of HM. It is observed that for high resolution sequences, the integer sample ME process can be speed-up by factors varying from 3.2 to 7.6, resulting in the bit-rate overhead of 1.5% and 0.6% for Random Access (RA) and Low Delay P (LDP) configurations, respectively. In addition, the similar speed-up is observed for sequences with mainly Computer-Generated Imagery (CGI) content while trading off the bit rate overhead of up to 5.2%.