One-Point Hexagonal Inner Search for Fast Motion Estimation

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• 作者：Chorng-Yann Su ; Cheng-Tao Chang
• 刊名：Lecture Notes in Computer Science
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：3804
• 期：1
• 页码：pp.406-412
• 全文大小：200 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In this paper, we propose a novel inner search algorithm for fast motion estimation to speed up the coding of video compression. The proposed algorithm, called as one-point hexagonal inner search (OPHIS), is based on the characteristic of monotonically decreasing of distortion on a local area. The most probable inner point is checked when an inner search starts. Compared with the enhanced hexagon-based search algorithm (EHEXBS), the OPHIS not only decreases the number of search points but also gets a better video quality. Experimental results show that the speed improvement is about 12.06% on average and the percentage decrease of the mean squared error is near to 2.29% on average. Therefore, the proposed OPHIS is more suitable for the applications of fast motion estimation than the EHEXBS.