A High Performance Reconfigurable Motion Estimation Hardware Architecture

被引:0
|
作者
Tasdizen, O. [1 ]
Kukner, H. [1 ]
Akin, A. [1 ]
Hamzaoglu, I. [1 ]
机构
[1] Sabanci Univ, Fac Engn & Nat Sci, TR-34956 Istanbul, Turkey
关键词
SEARCH ALGORITHM; PATTERN;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. For the recently available high definition frame sizes and high frame rates, the computational complexity of full search (FS) ME algorithm is prohibitively high, while the PSNR obtained by fast search ME algorithms is low. Therefore, in this paper, we propose a new A E algorithm and a high performance reconfigurable systolic A E hardware architecture for efficiently implementing this algorithm. The proposed A E algorithm performs up to three different granularity search iterations in different size search ranges based on the application requirements. Simulation results showed that the proposed ME algorithm performs very close to FS algorithm, even though it searches much fewer search locations than FS algorithm. It outperforms successful fast search ME algorithms by searching more search locations than these algorithms. The proposed reconfigurable ME hardware is implemented in VHDL and mapped to a low cost Xilinx XC3S1500-5 FPGA. It works at 130MHz and is capable of processing high definition and high frame rate video formats in real time. Therefore, it can be used in flat panel displays for frame rate conversion and de-interlacing, and in video encoders.
引用
收藏
页码:882 / 885
页数:4
相关论文
共 50 条
  • [41] A high performance reconfigurable hardware platform for digital pulse processing
    Cardoso, JM
    Simoes, JB
    Correia, CMBA
    Combo, A
    Pereira, R
    Sousa, J
    Cruz, N
    Carvalho, P
    Varandas, CAF
    IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2004, 51 (03) : 921 - 925
  • [42] On buffer management strategies for high performance computing with reconfigurable hardware
    Martinez, Guillermo Marcus
    Lienhart, Gerhard
    Kugel, Andreas
    Maenner, Reinhard
    2006 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS, PROCEEDINGS, 2006, : 343 - 348
  • [43] High Performance Phylogenetic Analysis With Maximum Parsimony on Reconfigurable Hardware
    Kasap, Server
    Benkrid, Khaled
    IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2011, 19 (05) : 796 - 808
  • [44] High-Performance Stateful Intrusion Detection in Reconfigurable Hardware
    Yoon, Seungyong
    Kim, Byoungkoo
    Oh, Jintae
    JOURNAL OF INFORMATION ASSURANCE AND SECURITY, 2007, 2 (01): : 68 - 74
  • [45] A Partially Reconfigurable Architecture Supporting Hardware Threads
    Wang, Ying
    Yan, Jian
    Zhou, Xuegong
    Wang, Lingli
    Luk, Wayne
    Peng, Chenglian
    Tong, Jiarong
    2012 INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (FPT'12), 2012, : 269 - 276
  • [46] Dynamic hardware plugins: exploiting reconfigurable hardware for high-performance programmable routers
    Taylor, DE
    Turner, JS
    Lockwood, JW
    Horta, EL
    COMPUTER NETWORKS, 2002, 38 (03) : 295 - 310
  • [47] RNA: A Reconfigurable Architecture for Hardware Neural Acceleration
    Tu, Fengbin
    Yin, Shouyi
    Ouyang, Peng
    Liu, Leibo
    Wei, Shaojun
    2015 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2015, : 695 - 700
  • [48] A Reconfigurable Hardware Architecture for Fractional Pixel Interpolation in High Efficiency Video Coding
    Diniz, Claudio M.
    Shafique, Muhammad
    Bampi, Sergio
    Henkel, Joerg
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2015, 34 (02) : 238 - 251
  • [49] A Novel Reconfigurable Hardware Architecture of Neural Network
    Khalil, Kasem
    Eldash, Omar
    Dey, Bappaditya
    Kumar, Ashok
    Bayoumi, Magdy
    2019 IEEE 62ND INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS), 2019, : 618 - 621
  • [50] Efficient Architecture for Spike Sorting in Reconfigurable Hardware
    Hwang, Wen-Jyi
    Lee, Wei-Hao
    Lin, Shiow-Jyu
    Lai, Sheng-Ying
    SENSORS, 2013, 13 (11): : 14860 - 14887