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One-Point Hexagonal Inner Search for Fast Motion Estimation

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Advances in Visual Computing (ISVC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3804))

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Abstract

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.

Index Terms: one-point hexagonal inner search, fast motion estimation, hexagonal search, enhanced hexagon-based search algorithm.

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© 2005 Springer-Verlag Berlin Heidelberg

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Su, CY., Chang, CT. (2005). One-Point Hexagonal Inner Search for Fast Motion Estimation. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_49

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  • DOI: https://doi.org/10.1007/11595755_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30750-1

  • Online ISBN: 978-3-540-32284-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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