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In this paper, a hierarchical prediction scheme for fast motion search is proposed in order to implement an effective encoder that pays a small amount of search cost to achieve the best match without little rate-distortion performance degradation. The proposed method has a hierarchical tree structure, where each node has two sub-tasks; namely, the reference frame selection and the spatial search region prediction. From now on, let’s call best motion vector by full search as true motion vector. Proposed fast motion search for multiple reference frames can be summarized as:
Step1. Initial searching point in previous frame: In literature, majority of true motion vectors are distributed around the center of searching window in recent frames so we first search the previous frame. Diamond search fails to search the true motion when the initial point misleads search path to local minima. In order to solve this problem, initial points are searched based on multiresolution motion search.
Step2. Perform diamond search for each initial points and compare the minimum distortion measure with stopping criterion which defines maximum searching points, minimum diamond size and threshold based on QP. If the stopping criterion is met, then motion search is finished with the motion vector having minimum distortion. Otherwise go to Step 3. Here, the diamond size depends on the motion activity between current frame (T) and previous frame (T-1).
Step3. Find out search center in the frame indicated by motion trace (motion vector field obtained from previous encoding stage) for all best points in each diamonds in previous frame (T-1). Based on its motion activity, the diamond size is determined and checked the stopping criterion for all diamond in second previous frames. Iterate this step until the stopping condition is met.
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