arrow
Return

High Performance Hardware Architectures for One Bit Transform Based Single and Multiple Reference Frame Motion Estimation

delete2010-05-01
delete12
PRE
AI
A
Abdulkadir Akın *
G
Gokhan Sayilar
H
Hamzaoglu, Ilker
DOI:10.1109/TCE.2010.5506051delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. One bit transform (1BT) based ME algorithms have low computational complexity. Therefore, in this paper, we propose high performance systolic hardware architectures for 1BT based fixed block size (FBS) single reference frame (SRF) ME, variable block size (VBS) SRF ME, and multiple reference frame (MRF) ME. The proposed FBS-SRF ME hardware performs full search ME for 4 Macroblocks in parallel and it is faster than the 1BT based ME hardware reported in the literature. In addition, it uses less on-chip memory than the previous 1BT based ME hardware by using a novel data reuse scheme and memory organization. The proposed VBS-SRF ME hardware is also faster and uses less on-chip memory than previous 1BT based VBS-SRF ME hardware. The proposed MRF ME hardware is the first 1BT based MRF ME hardware in the literature. In order to trade-off ME performance and computational complexity, the proposed MRF ME hardware is designed as reconfigurable in order to statically configure the number and selection of reference frames based on the application requirements. The proposed hardware architectures are implemented in Verilog HDL. They are capable of processing 83 1920x1080 full High Definition frames per second. Therefore, they can be used in consumer electronics products that require real-time video processing or compression.(1)
Keywords:
Motion Estimation
Multiple Reference Frame
One Bit Transform
Hardware Implementation
FPGA

Journal

IEEE Transactions on Consumer Electronics cover
IEEE Transactions on Consumer Electronics
IF:
10.9
Papers:
5.3K
Citations:
6.8K

Organization

S
Sabanci University
Scholars:
2.8K
Papers: 2.6K
Citations: 12
Cited Papers

Cited Papers

An All Binary Sub-Pixel Motion Estimation Approach and its Hardware Architecture
err2008-11-01
err22
PREAI
errCelebi, Anil; Akbulut, Orhan; Urhan, Oguzhan; Hamzaoglu, Ilker; Ertuerk, Sarp
errShare
errSave
err
IF0
err
err0
PREAI
err
errShare
errSave
Fast Reference Frame Selection Algorithm for H.264/AVC
err2009-05-01
err12
PREAI
errLee, Kangjun; Jeon, Gwanggil; Jeong, Jechang
errShare
errSave
errShare
errSave
researcher View more