• DocumentCode
    2487654
  • Title

    Extending depth of field by intrinsic mode image fusion

  • Author

    Hariharan, Harishwaran ; Koschan, Andreas ; Abidi, Mongi

  • Author_Institution
    Imaging, Robot. & Intell. Syst. Lab., Univ. of Tennessee, Knoxville, TN
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Here, a versatile data-driven application independent method to extend the depth of field is presented. The principal contribution in this effort is the use of features extracted by empirical mode decomposition, namely Intrinsic Mode Images, for fusion. The input images are decomposed into intrinsic mode images and fusion is performed on the extracted oscillatory modes, by means of weighing schemes that allow emphasis of focused regions in each input image. The fused image unifies information from all focal planes, while maintaining the verisimilitude of the scene. In order to validate the fusion performance of our method, we have compared our results with those of region-based and multiscale decomposition based fusion techniques. Several illustrative examples and objective comparisons are provided.
  • Keywords
    Hilbert transforms; feature extraction; image fusion; depth of field; empirical mode decomposition; features extraction; intrinsic mode image fusion; versatile data-driven application independent method; Data mining; Feature extraction; Focusing; Image fusion; Image segmentation; Inspection; Intelligent robots; Kernel; Layout; Microscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761727
  • Filename
    4761727