Real-time restoration of motion-blurred video images on GPU

WANG Jing; LI Shi

doi:10.3788/OPE.20101810.2262

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Real-time restoration of motion-blurred video images on GPU

Article | 更新时间：2020-08-12

- Real-time restoration of motion-blurred video images on GPU
- Optics and Precision Engineering Vol. 18, Issue 10, Pages: 2262-2268(2010)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春130033
  2. 杭州电子科技大学图形图像研究所,浙江杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20101810.2262
  CLC： TN941.1;TP391.4
- Received：07 June 2010，
  
  Revised：06 August 2010，
  
  Published Online：28 October 2010，
  
  Published：20 October 2010
- 稿件说明：
移动端阅览
王晶, 李仕. 运动模糊视频图像在图形处理器平台上的实时恢复[J]. 光学精密工程, 2010,18(10): 2262-2268

WANG Jing, LI Shi. Real-time restoration of motion-blurred video images on GPU[J]. Editorial Office of Optics and Precision Engineering , 2010,18(10): 2262-2268
王晶, 李仕. 运动模糊视频图像在图形处理器平台上的实时恢复[J]. 光学精密工程, 2010,18(10): 2262-2268 DOI： 10.3788/OPE.20101810.2262.

WANG Jing, LI Shi. Real-time restoration of motion-blurred video images on GPU[J]. Editorial Office of Optics and Precision Engineering , 2010,18(10): 2262-2268 DOI： 10.3788/OPE.20101810.2262.

摘要

提出了一种图形处理器优化编程方法

用于实现运动模糊视频图像的实时恢复处理。根据计算统一设备架构(CUDA)的硬件框架特征对GPU的线程块及线程数量进行优化配置

并引入了一种自动内存接合访问的方法

使得GPU的硬件资源得到充分利用。根据图像频谱的对称性去除冗余信息

减少了图像算法在频谱滤波时的数据量

使得GPU对内存的访问次数下降

从而提升了算法效率。实验表明

本文提出的GPU方案的计算性能比传统的CPU平台方案提升了一个数量级

半频谱滤波设计使总时间开销减少20％以上

实验结果证明了本文方案的可行性及有效性。

Abstract

A Graphic processing Unit(GPU) optimization programming method is presented to apply to the real-time restoration of motion blurred video images. The blocks and threads run on the GPU are optimally set based on the hardware structure of Compute Unified Device Architecture (CUDA)

and a memory access method is introduced to implement automatic coalesced access. These are required to make sure the full utilization of the GPUs hardware resource. According to the symmetry property of FFT spectra

the redundant information in the frequency spectrum is eliminated and the number of frequency data filtered by the image algorithm is decreased

by which the amount of GPU memory access for realizing the algorithm optimization is reduced and the computing efficiency is improved. The experiment indicates that the proposed GPU project can improve the computing performance by 10 times as compared with the conventional CPU project

and the design of half-spectrum filtering can reduce the above time consumption by 20%. The experimental results confirm the feasibility and the validity of proposed method.

关键词

Keywords

references

吴恩华. 图形处理器用于通用计算的技术、现状及其挑战[J]. 软件学报, 2004,15(10):1493-1504.WU E H. State of the art and future challenge on general purpose computation on GPU [J]. Journal of Software, 2004,15(10):1493-1504. (in Chinese)[2] MORELAND K, ANGEL E. The FFT on a GPU [J]. Proceedings of the ACM SIGGRAPH/Eurographics Conference on Graphics Hardware, San Diego, 2003:112-119.[3] KRUGER J, WESTERMANN R. Linear algebra operators for GPU implementation of numerical algorithms [J]. ACM Transactions on Graphics, 2003,22(3):908-916.[4] BOLZ J, FARMER I, GRINSPUN E, et al.. Sparse matrix solvers on the GPU: Conjugate gradients and multigrid [J]. ACM Transactions on Graphics, 2003,22(3):917-924.[5] HARRIS M J , BAXTER W V, SCHEUERMANN T, et al..Simulation of cloud dynamics on graphics hardware .Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Workshop on Graphics Hardware, San Diego, 2003:92-101.[6] CUNTZ N, KOLB A, STRZODKA R, et al.. Particle level set advection for the interactive visualization of unsteady 3D flow .Proceedings of the Eurographics/IEEE-VGTC Symposium on Visualization, Eindhoven, 2008:719-726.[7] ZHOU K, HOU Q M, WANG R, et al.. Real-time Kd-tree construction on graphics hardware [J]. ACM Transactions on Graphics, 2008,21(5):231-241.[8] 贾平,张葆,孙辉. 航空成像像移模糊恢复技术[J]. 光学精密工程,2006,14(4):697-703. JIA P, SUN H, ZHANG B. Restoration of motion-blurred aerial image [J]. Opt. Precision Eng., 2006,14(4):697-703. (in Chinese)[9] BIENOND J, RIESKE J, GERBRANDS J J. A fast Kalman filter for images degraded by both blur and noise[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1983,31(5):1248-1256.[10] LIKHTEROV B, KOPEIKA N S. Motion-blurred image restoration using modified inverse all-pole filters.[J]. Journal of Electronic Image, 2004,13(2):257-263.[11] BANHAM M R, KATSAGGELGS A K. Digital image restoration[J]. IEEE signal proc. mag.,1997,14(2):24-41.[12] OWENS J D, HOUSTON M, LUEBKE D, et al.. GPU computing . IEEE Proceedings,2008:879-899.[13] NVIDIA CUDA programming guide. Version 3.0 [M]. Santa Clara : NVIDIA Corporation, 2010.[14] OWENS J D, LUEBKE D, GOVINDARAJU N, et al.. A survey of general-purpose computation on graphics hardware[J]. Computer Graphics forum, 2007,26(1):80-113.[15] SMITH S W. The Scientist and Engineer's Guide to Digital Signal Processing[M]. California:California Technical Publishing,1997.[16] 李仕,孙辉,张葆. 运动模糊图像的实时恢复算法[J]. 光学精密工程,2007,15(5):767-772. LI SH, SUN H, ZHANG B. Restoration of motion-blurred images [J].Opt. Precision Eng., 2007,15(5):767-772.(in Chinese)[17] TAN K C, LIM H, TAN B T G. Restoration of real-world motion-blurred images [J]. CVGIP, 1991,53:291-299.[18] TAN K C, LIM H, TAN B T G. Windowing techniques for image restoration [J]. CVGIP, 1991,53:491-500.

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