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ROI based complexity reduction algorithm for H.264 encoder

Authors: Tianruo Zhang; Satoshi Goto; Chen Liu; Minghui Wang; Xin Jin;

ROI based complexity reduction algorithm for H.264 encoder

Abstract

This paper proposes a region-of-interest (ROI) based H.264/AVC encoder which reduces computational complexity. A proposed fast ROI detection algorithm which can detect face-like regions as ROIs is applied to obtain accurate and small ROI so as to reduce the necessary coding effort of the encoder. The complexity reduction algorithm contains 3 methods: (1) the inter prediction mode selection based on quality difference and ROI status, (2) unequal coding efficiency degradation based on unequal bits allocation, and (3) the ROI boundary enhancement to reduce the coding complexity of center MBs of ROI. Experimental results show that proposed novel ROI detection and complexity reduction scheme can reduce 76.10% simulation time when QP difference between ROI and non-ROI is 20. Compared with previous work, 19.09% of encoding time is further reduced with similar performance degradation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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