基于改进粒子群优化的视频编码块匹配运动估计技术

Deepak Singh
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引用次数: 0

摘要

在视频编码中,利用单模态误差曲面的基于块匹配的运动估计(BMME)方案以其易于实现而广受欢迎。然而,许多真实世界的视频序列在块搜索窗口中表现出多个局部最小值。提出了一种基于模式的改进粒子群优化运动估计方法(PMPSO-ME)。基于种群的进化方法;粒子群算法保证了全局最优解,避免陷入局部最小值。在H.264/AVC平台的JM 18.6参考软件上对该技术进行了分析。从搜索点数量、编码时间复杂度、比昂特加德度量等方面对该方法进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Block Matching Motion Estimation Technique using Modified Particle Swarm Optimization in Video Coding
In video coding, the block matching based motion estimation (BMME) schemes by exploiting the uni-modal error surface is quite popular for easy implementation. Though, many real-world video sequences exhibit multiple local minima within the block search window. This research article proposes a pattern based modified particle swarm optimization approach for motion estimation (PMPSO-ME). The population-based evolutionary method; PSO ensures the global optimum solution and avoids trapping into local minima.The proposed technique is analyzed on JM 18.6 reference software of H.264/AVC platform. The proposed technique is evaluated for compared with the state-of-the-art approaches in terms of number of search points, encoding time complexity, Bjontegaard metrics etc.
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