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 E...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.展开更多
This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for ...This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.展开更多
文摘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.
文摘This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.
