• DocumentCode
    3161198
  • Title

    An improved focusing algorithm based on image definition evaluation

  • Author

    Hui, Li ; Chengyu, Fu

  • Author_Institution
    Inst. Of Opt. & Electron., Grad. Univ. Of Chinese Acad. Of Sci., Chengdu, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    3743
  • Lastpage
    3746
  • Abstract
    In order to overcome the limitations of traditional focusing function, the reasons why traditional approach lower the focusing precision are analyzed, and a theory based on curve fitting and probabilistic model is proposed. This algorithm can effectively improve the limitations that one focusing function is applicable to one type of image only, so that the classical image definition evaluation function are able to determine the focal position. We accomplished some experiments based on the images obtained from the CCD of the lab. Experimental results show that the proposed focusing algorithm based on definition evaluation function has an excellent focusing performance, good noise immunity and practical applications.
  • Keywords
    curve fitting; image processing; probability; curve fitting; focal position; focusing function; focusing precision; image definition evaluation function; improved focusing algorithm; noise immunity; probabilistic model; Charge coupled devices; Curve fitting; Focusing; Image sequences; Interference; Noise; Auto Focus; focusing algorithm; image definition evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6009938
  • Filename
    6009938