摘要
In this paper, we proposed a novel Two-layer Motion Estimation(TME) which searches motion vectors on two layers with partial distortion measures in order to reduce the overwhelming computational complexity of Motion Estimation(ME) in video coding. A layer is an image which is derived from the reference frame such that the sum of a block of pixels in the reference frame determines the point of a layer. It has been noticed on different video sequences that many motion vectors on the layers are the same as those searched on the reference frame. The proposed TME performs a coarse search on the first layer to identify the small region in which the best candidate block is likely to be positioned and then perform local refined search on the next layer to pick the best candidate block in the located small area. The key feature of TME is its flexibility of mixing with any fast search algorithm. Experimental results on a wide variety of video sequences show that the proposed algorithm has achieved both fast speed and good motion prediction quality when compared to well known as well as the state-of-the-art fast block matching algorithms.
In this paper,we proposed a novel Two-layer Motion Estimation （TME） which searches motion vectors on two layers with partial distortion measures in order to reduce the overwhelming computational complexity of Motion Estimation （ME） in video coding.A layer is an image which is derived from the reference frame such that the sum of a block of pixels in the reference frame determines the point of a layer.It has been noticed on different video sequences that many motion vectors on the layers are the same as those searched on the reference frame.The proposed TME performs a coarse search on the first layer to identify the small region in which the best candidate block is likely to be positioned and then perform local refined search on the next layer to pick the best candidate block in the located small area.The key feature of TME is its flexibility of mixing with any fast search algorithm.Experimental results on a wide variety of video sequences show that the proposed algorithm has achieved both fast speed and good motion prediction quality when compared to well known as well as the state-of-the-art fast block matching algorithms.
