Fast Motion Estimation System Using Dynamic Models for H.264/AVC Video Coding

  • Authors:
  • Yasser Ismail;Jason B. McNeely;Mohsen Shaaban;Hanan Mahmoud;Magdy A. Bayoumi

  • Affiliations:
  • Department of Electronics and Communications, Faculty of Engineering, Mansoura University, Mansoura, Egypt;Alaska University, Fairbanks, AK, USA;University of Louisiana at Lafayette, Lafayette, LA, USA;Research Unit, Department of Information Technology, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;University of Louisiana at Lafayette, Lafayette, LA, USA

  • Venue:
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Year:
  • 2012

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Abstract

H.264/AVC offers many coding tools for achieving high compression gains of up to 50% more than other standards. These tools dramatically increase the computational complexity of the block based motion estimation (BB-ME) which consumes up to 80% of the entire encoder's computations. In this paper, computationally efficient accurate skipping models are proposed to speed up any BB-ME algorithm. First, an accurate initial search center (ISC) is decided using a smart prediction technique. Thereafter, a dynamic early stop search termination (DESST) is used to decide if the block at the ISC position can be considered as a best match candidate block or not. If the DESST algorithm fails, a less complex style of the motion estimation algorithm which incorporates dynamic padding window size technique will be used. Further reductions in computations are achieved by combining the following two techniques. First, a dynamic partial internal stop search technique which utilizes an accurate adaptive threshold model is exploited to skip the internal sum of absolute difference operations between the current and the candidate blocks. Second, a dynamic external stop search technique greatly reduces the unnecessary operations by skipping all the irrelevant blocks in the search area. The proposed techniques can be incorporated in any block matching motion estimation algorithm. Computational complexity reduction is reflected in the amount of savings in the motion estimation encoding time. The novelty of the proposed techniques comes from their superior saving in computations with an acceptable degradation in both peak signal-to-noise ratio (PSNR) and bit-rate compared to the state of the art and the recent motion estimation techniques. Simulation results using H.264/AVC reference software (JM 12.4) show up to 98% saving in motion estimation time using the proposed techniques compared to the conventional full search algorithm with a negligible degradation in the PSNR by approximately 0.05 dB and a small increase in the required bits per frame by only 2%. Experimental results also prove the effectiveness of the proposed techniques if they are incorporated with any fast BB-ME technique such as fast extended diamond enhanced predictive zonal search and predictive motion vector field adaptive search technique.