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A Pattern-Based Artificial Bee Colony Algorithm for Motion Estimation in Video Compression Techniques

机译:视频压缩技术中基于模式的人工蜂群运动估计算法

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Block matching (BM) motion estimation plays an inevitable role in video coding applications. BM approaches are used for data compression. The compression is achieved by removing the temporal redundancy in the video sequences. In the BM process, each video frame is subdivided into macroblocks. Each macroblock in the current frame is compared with the previous frame. The main objective is to minimize sum absolute difference. In this work, some modifications have been performed on conventional artificial bee colony algorithm to improve the conventional BM systems. An initial pattern is used in the proposed algorithm to reduce the computational cost. The computational cost is represented in terms of search points and convergence time. Experimental results results show the improvement for the proposed approach over other block matching algorithms in terms of the performance measures.
机译:块匹配(BM)运动估计在视频编码应用中扮演着不可避免的角色。 BM方法用于数据压缩。通过去除视频序列中的时间冗余来实现压缩。在BM处理中,每个视频帧被细分为宏块。将当前帧中的每个宏块与前一帧进行比较。主要目的是使和绝对差最小。在这项工作中,对常规的人工蜂群算法进行了一些修改,以改进常规的BM系统。在所提出的算法中使用初始模式以减少计算成本。计算成本用搜索点和收敛时间表示。实验结果表明,相对于其他块匹配算法,该方法具有更好的性能指标。

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