Low-Power H.264 Video Compression Architectures for Mobile Communication

A. Bahari, Tughrul Arslan

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a method to reduce the computation and memory access for variable block size motion estimation (ME) using pixel truncation. Previous work has focused on implementing pixel truncation using a fixed-block-size (16 times 16 pixels) ME. However, pixel truncation fails to give satisfactory results for smaller block partitions. In this paper, we analyze the effect of truncating pixels for smaller block partitions and propose a method to improve the frame prediction. Our method is able to reduce the total computation and memory access compared to conventional full-search method without significantly degrading picture quality. With unique data arrangement, the proposed architectures are able to save up to 53% energy compared to the conventional full-search architecture. This makes such architectures attractive for H.264 application in future mobile devices.
Original languageEnglish
Pages (from-to)1251 - 1261
Number of pages11
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume19
Issue number9
DOIs
Publication statusPublished - 1 Sep 2009

Fingerprint

Dive into the research topics of 'Low-Power H.264 Video Compression Architectures for Mobile Communication'. Together they form a unique fingerprint.

Cite this