Abstract
Recently, an enhanced hexagon-based (EHS) search algorithm was proposed to speedup the original hexagon-based search (HS) using a 6-side-based fast inner search. However, this 6-side-based method is quite irregular by inspecting the distance between the inner search points and the coarse search points that would lower prediction accuracy. In this paper, a new point-oriented grouping strategy is proposed to develop fast inner search techniques for speeding up the HS and diamond search (DS) algorithms. Experimental results show that the new HS and DS using point-oriented inner searches are faster than their original algorithms up to 30% with negligible peak signal-to-noise ratio degradation
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