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In this work, we develop a fast binary partition tree based variable size video coding system. New adaptive algorithms proposed herein are applied to a video encoder with binary partition trees. First, to reduce the computation for block-matching, an adaptive search area method is described which adjusts the searching region according to the size of each block. Second, an early termination method...
In this paper, a new block-based motion estimation (ME) method is proposed which uses the Kalman filtering (KF) with adaptive block partitioning (ABP) to improve the motion estimates resulting from conventional block-matching algorithms (BMAs). In our method, a first order autoregressive model is applied to the motion vectors (MVs) obtained by BMAs. The motion correlations between neighboring blocks...
This paper presents a new adaptive Kalman filtering method to improve the performance of block-based motion estimation. In our work, measured motion vectors are obtained by a conventional block-matching algorithm (BMA). A first order autoregressive model is employed to fit the motion correlation between neighboring blocks and then to achieve the predicted motion information. To further improve the...
In this work, a new block-based motion estimation method using the adaptive Kalman filtering (KF) based on one-dimensional (1-D) and two-dimensional (2-D) autoregressive (AR) models is proposed to improve the motion estimates. Conventional block-matching algorithms (BMAs) are utilized to obtain the measured motion vectors (MVs). Autoregressive models are employed to characterize the motion correlation...
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