Fast phase-based registration of multimodal image data
Signal Processing
SaVE: sensor-assisted motion estimation for efficient h.264/AVC video encoding
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Exploiting transitivity of correlation for fast template matching
IEEE Transactions on Image Processing
Adaptive two-step adjustable partial distortion search algorithm for motion estimation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Efficient starting point decision for enhanced hexagonal search
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Estimation of motion vector parameter using hexagon-diamond search algorithm
Journal of Real-Time Image Processing
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The quality control for video coding usually absents from many traditional fast block motion estimators. A novel block-matching algorithm for fast motion estimation named the adjustable partial distortion search algorithm (APDS) is proposed. It is a new normalized partial distortion comparison method capable of adjusting the prediction accuracy against searching speed by a quality factor k. With adjustability, APDS could act as the normalized partial distortion search algorithm (NPDS) when k is equal to 0, and the conventional partial distortion search algorithm (PDS) when k is equal to 1. In addition, it uses a halfway-stop technique with progressive partial distortions (PPD) to increase early rejection rate of impossible candidate motion vectors at very early stages. Simulations with PPD reduce computations up to 38 times with less than 0.50-dB degradation in PSNR performance, as compared to the full-search algorithm (FS). Experimental results show that APDS could provide peak signal-to-noise ratio performance very close to that of FS with speedup ratios of 7 to 16 times, and close to that of NPDS from 22 to 32 times, respectively, as compared to FS.