Coarse-to-fine partial distortion search algorithm for motion estimation

Chia Hung Yeh; Ming Te Wu; Shiunn Jang Chern

Coarse-to-fine partial distortion search algorithm for motion estimation

Chia Hung Yeh^*, Ming Te Wu, Shiunn Jang Chern

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

This study proposes a coarse-to-fine partial distortion search algorithm for motion estimation to accurately predict the minimum distortion region. In the proposed method, the distortion behavior is first analyzed in a search window to indicate the possible occurrence region of the global minimum distortion position. Normalized partial distortion searching is then performed on the selected region, instead of the whole search window. The proposed algorithms have a low computational complexity yet do not degrade the PSNR significantly.

Original language	English
Pages (from-to)	2523-2530
Number of pages	8
Journal	International Journal of Innovative Computing, Information and Control
Volume	5
Issue number	9
Publication status	Published - 2009 Sept
Externally published	Yes

Keywords

Block-matching distortion
Full search
Motion estimation
Normalized partial distortion search
Sum of absolute difference

ASJC Scopus subject areas

Software
Theoretical Computer Science
Information Systems
Computational Theory and Mathematics

Cite this

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title = "Coarse-to-fine partial distortion search algorithm for motion estimation",

abstract = "This study proposes a coarse-to-fine partial distortion search algorithm for motion estimation to accurately predict the minimum distortion region. In the proposed method, the distortion behavior is first analyzed in a search window to indicate the possible occurrence region of the global minimum distortion position. Normalized partial distortion searching is then performed on the selected region, instead of the whole search window. The proposed algorithms have a low computational complexity yet do not degrade the PSNR significantly.",

keywords = "Block-matching distortion, Full search, Motion estimation, Normalized partial distortion search, Sum of absolute difference",

author = "Yeh, {Chia Hung} and Wu, {Ming Te} and Chern, {Shiunn Jang}",

year = "2009",

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AU - Yeh, Chia Hung

AU - Wu, Ming Te

AU - Chern, Shiunn Jang

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N2 - This study proposes a coarse-to-fine partial distortion search algorithm for motion estimation to accurately predict the minimum distortion region. In the proposed method, the distortion behavior is first analyzed in a search window to indicate the possible occurrence region of the global minimum distortion position. Normalized partial distortion searching is then performed on the selected region, instead of the whole search window. The proposed algorithms have a low computational complexity yet do not degrade the PSNR significantly.

AB - This study proposes a coarse-to-fine partial distortion search algorithm for motion estimation to accurately predict the minimum distortion region. In the proposed method, the distortion behavior is first analyzed in a search window to indicate the possible occurrence region of the global minimum distortion position. Normalized partial distortion searching is then performed on the selected region, instead of the whole search window. The proposed algorithms have a low computational complexity yet do not degrade the PSNR significantly.

KW - Block-matching distortion

KW - Full search

KW - Motion estimation

KW - Normalized partial distortion search

KW - Sum of absolute difference

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JO - International Journal of Innovative Computing, Information and Control

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ER -

Coarse-to-fine partial distortion search algorithm for motion estimation

Abstract

Keywords

ASJC Scopus subject areas

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