• DocumentCode
    1740851
  • Title

    Modeling and restoration of Raman microscopic images

  • Author

    Ling, Jian ; Bovik, Alan C.

  • Author_Institution
    Dept. of Bioeng., Southwest Res. Inst., San Antonio, TX, USA
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    428
  • Abstract
    Presents a model for Raman microscopic images. The model describes the degradation of Raman signals by non-uniform illumination, by the microscopic system, and by additive signal-dependent Gaussian noise. Using this model, synthetic images were created to validate the model. Based on these synthetic images, an anisotropic diffusion filter was applied to reduce the signal-dependent Gaussian noise and at the same time not blur the objects´ boundary. A Wiener filter was used to restore the blurred Raman images by the microscopic system. And, an image ratioing method was used to correct for the non-uniform illumination. After the restoration, the mean absolute error between the restored image and the true image was minimized
  • Keywords
    Wiener filters; cellular biophysics; image restoration; medical image processing; modelling; optical microscopy; Raman microscopic images modeling; Raman microscopic images restoration; Raman signals degradation; additive signal-dependent Gaussian noise; anisotropic diffusion filter; blurred Raman images; drug distribution within cancer cell; image ratioing method; mean absolute error; microscopic system; nonuniform illumination; signal-dependent Gaussian noise; synthetic images; true image; Chemical technology; Degradation; Drugs; Frequency estimation; Image restoration; Lighting; Microscopy; Optical imaging; Raman scattering; Signal restoration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2000. Proceedings. 2000 International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-6297-7
  • Type

    conf

  • DOI
    10.1109/ICIP.2000.899425
  • Filename
    899425