期刊文献+

一种适用于硬件实现的宽动态图像合成算法 被引量:1

HDR Synthesis Algorithm Suitable for Hardware Implementation
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摘要 针对现有宽动态合成算法因复杂度高而难以应用于实时系统的缺点,提出一种有效且复杂度低、适合硬件实现的实时宽动态图像合成方法。算法首先获取同一场景两副不同曝光量的照片,通过使用线性的亮度映射函数T,从短曝光图像对应区域的信息恢复出长曝光图像中过曝区域的信息。该算法只需利用两幅原始图像,所需数据量少,且无须恢复图像中的亮度与曝光比信息,计算复杂度很低。同时,T用线性关系表示更易于硬件实现。实验表明,算法能够实现良好的宽动态图像效果。 For the complexity of the existing wide dynamic synthesis algorithm, which is difficult to apply to the real-time systems such as video surveillance,a synthesis method is proposed which is very efficient with low complexity,while suitable for the wide dynamic image of hardware implementation. Firstly the proposed algorithm gets two images of the same scene at different exposures. The missing information of long-exposure image can be restored from the information of corresponding area in the short-exposure image with the intensity value mapping function T. The proposed algorithm uses only two original images, which means the amount of data is less,without the need to restore the radiometric response function and the exposure rate,and the computational complexity is low. Meanwhile, the linear representation of T is more conductive to the hardware implementation. The experimental results show that the effect of the synthetic wide dynamic image is satisfactory.
出处 《电视技术》 北大核心 2013年第11期47-50,共4页 Video Engineering
基金 国家自然科学基金项目(60902052) 西北工业大学研究生创业种子基金项目(z2012093) 教育部博士点基金项目(20096102120032)
关键词 WDR 多次曝光 最小二乘法 动态范围扩展 累计直方图 WDR multiple exposure least square method dynamic range extension accumulated histogram
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参考文献12

  • 1程郑兴.数据拟合[M]陕西:西安交通大学出版社,1986.
  • 2郑世宝.智能视频监控技术与应用[J].电视技术,2009,33(1):94-96. 被引量:68
  • 3蔡波.视频实时图像处理系统研究及设计[J].电视技术,2005,29(5):23-25. 被引量:6
  • 4杨俊,王润生.智能化交通视频图像处理技术研究[J].电视技术,2006,30(9):74-77. 被引量:14
  • 5MANN S, PICARD R W. On Being 'undigital' with digital camer- as: Extending dynamic range by tom|fining differently exposed pie- tnres[C]//Proe. IS&T 46th Annual Con/:rence. [S.I.]: IS&T, 1995. DEBEVEC P E,.
  • 6MAL1K J. Recovering high dynamic range radiance maps fn*m photographs IEB/OL1. 12012-08-02]. lattp://www.patnlde- bevec.eom/Research/H D R/.
  • 7MITSUNAGA T, NAYAR S K. Radiometrie self calibrationlC]//Pn:e. IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1999. [S.I.] : IEEE Press, 1999 : 374 - 380.
  • 8GROSSBERG M D, NAYAR S K. Determining the camera response from inmges: What Is knowable?[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,2003,25( I 1 ) : 1455 1467.
  • 9GROSSBERG M D, NAYAR S K. What is the spaee of camera re- sponse functions?[C]// Proc. Computer Society on Computer Vision and Pattern Recognition. New York, USA : IEEE Press, 2003 : 602 609.
  • 10GROSSBERG M D, NAYAR S K. What can be known about the ra- diometric response from images?[J].Lecture Notes in Computer Sci- ence, 2006(2356) : 393-413.

二级参考文献21

  • 1MICHALOPOULOS P.Vehicle detection through video image processing:the AUTOSCOPE system[J].IEEE Transaction on Vehicle Technology.1991(40):21-29.
  • 2KUMAR P.Framework for real-time behavior interpretation from traffic video[J].IEEE Transactions on intelligent transportation systems,2005,6(1):43-53.
  • 3HU W M,TAN T N,WANG L,et al.A survey on visual surveillance of object motion and behaviors[J].IEEE Transaction on Systems,Man,and Cybernetics-Part C:Application and Reviews 2004,34(3):334-352.
  • 4WANG Y K,CHEN S H.Robust vehicle detection approach[C]//Proc.IEEE Conference on Advanced Video and Signal Based Surveillance 2005.[S.l.]:IEEE Press.2005:117-122.
  • 5HAMPAPUR A,BROWN L,CONNELL J,et al.Smart surveillance:applications,technologies and implications,information,communications and signal processing[C]//Proceedings of the 2003 Joint Conference of the Fourth International Conference on.2003(2):1133-1138.
  • 6MARKOU M,SIHGH S.Novelty detection:a review,Part Ⅰ:statistical approaches[J].Signal Processing,2003,83(12):2481-2497.
  • 7MARKOU M,SIHGH S.Novelty detection:a review,Part 2:neural network based approaches[J].2003,83(12):2499-2521.
  • 8ITTI L,BALDI P.A surprising theory of attention[C]//Proc.IEEE Workshop on AIPR04,[S.l.]:IEEE Press.2004.
  • 9ROGER S G,VISHAL S V,VINEET S.C,et al.VENUS:a system for novelty detection in video streams with learning[C]//Proceedings of the 17th International FLAIRS Conference,SouthBeach:[s.n.],2004.
  • 10HUA Z,JIANBO S,VISONTAI M.Detecting unusual activity in video[C]//Proceedings of the 2004 IEEE Computer Society Conference on,2004(2):819-826.

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同被引文献8

  • 1DEBVEC P, MALIK J. Recovering high dynamic range radiance maps from photographs [ EB/OL ]. [ 2013 -09 -02 ]. http://wenku, baidu. conr/link? url = 6VhdAIQHKKoxCpmqg7ZTSKwiwMGYf5Sm3LT82y27 kEBIwRQdi6OTZh_DOCC8j VM - QI_ Q- qVvyfexX Dol 6dvVvKKWQcpxdk 0_XSGpr31zPW.
  • 2MERTENS T,KAUTZ J ,REETH F. Exposure fusion[ C ]//Proc. Pacific Conference on Computer Graphics and Applications. Hawaii, USA: [ s. n. ] ,2007:382-390.
  • 3BOGONI L. Extending dynamic range of monochrome and color images through fusion[ C]//Proc. International Conference on Pattern Recogni- tion(ICPR). [S. 1. ] :IEEE Press ,2000 :15-17.
  • 4KHAN E, AKYUZ A, REINHARD E. Ghost removal in high dynamic range images[ C]//Proc. IEEE International Conference on Image Pro- cessing. [ S. 1. ] :IEEE Press ,2006:2005-2008.
  • 5WARD G. Fast,robust image registration for compositing high dynanic range photographs from handheld exposures [ J ]. Journal of Graphics Tools ,2003 ( 8 ) : 17-30.
  • 6MANN S. Comparametric equations with practical applications in quanti- graphic image processing [ J ]. IEEE Trans. Image Processing, 2000,9(8) :1389-1406.
  • 7YEGANEH H, WANG Z. Objective quality assessment of tone mapped images[J]. IEEE Trans. Image Processing,2013,22(2) :657-667.
  • 8AN J, LEE S, KUK J,et al. A multi-exposure image fusion algorithm without ghost effect[ C]//Proe. IEEE International Conference on Acous- tics, Speech, and Signal Processing. [ S. 1. ]: IEEE Press, 2011: 1565-1568.

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