NDLI: Low Power Motion Estimation Design Based on Non-Uniform Pixel Truncation

Content Provider	Springer Nature Link
Author	Rong, Yaocheng Yu, Quanhe An, Da He, Yun
Copyright Year	2013
Abstract	Motion estimation (ME) consumes large hardware cost and power (50 %–90 %) in most video encoders. Thus reducing the power consumption of ME is a major concern of low power video encoder design. A lot of fast ME approaches have been proposed but many of them focus on algorithm speed up rather than power consumption. Pixel truncation can effectively reduce the hardware cost and the power consumption. Classical pixel truncation is usually performed uniformly within the search window. However, it suffers great compression efficiency degradation when high power reduction ratio is required. This paper proposes a low power motion estimation scheme based on non-uniform pixel truncation. By observing the unequal distribution of motion vectors, we divide the search window into different sub-regions and employ different numbers of truncated bits (NTB) in these sub-regions. NTB pairs are appropriately examined to achieve a better tradeoff between the compression efficiency and the hardware cost. Then hardware architecture is designed to evaluate the hardware cost of the algorithm and a carefully designed threshold parameter is introduced to make the algorithm more hardware-friendly. Test results demonstrate that the proposed hardware-friendly algorithm achieves 21 % and 49 % power saving in the 2D and 1D ME architecture, respectively, both with negligible compression efficiency degradation.
Starting Page	137
Ending Page	152
Page Count	16
File Format	PDF
ISSN	19398018
Journal	Journal of Signal Processing Systems
Volume Number	80
Issue Number	2
e-ISSN	19398115
Language	English
Publisher	Springer US
Publisher Date	2013-09-17
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Low power electronics Motion estimation Pixel truncation Power efficient Video coding VLSI architecture Signal, Image and Speech Processing Circuits and Systems Electrical Engineering Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Signal Processing Control and Systems Engineering Information Systems Modeling and Simulation Hardware and Architecture

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