• DocumentCode
    1594118
  • Title

    Segmentation based denoising using multiple compaction domains

  • Author

    Singh, Maneesh ; Ishwar, Prakash ; Ratakonda, Krishna ; Ahuja, Narendra

  • Author_Institution
    Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
  • Volume
    1
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    372
  • Abstract
    In this paper, we propose a novel segmentation based denoising algorithm. Segmentation yields intrinsically homogeneous and extrinsically heterogeneous regions. A denoising algorithm that uses Multiple Compaction Domains (MCD) is then applied on each of the resulting segments. Such a scheme retains important perceptual information in the segment boundaries while the denoising algorithm operates only on homogeneous segments. Further, the MCD algorithm is demonstrably superior to the classical denoising algorithms using transform domain thresholding. Our algorithm yields better perceptual quality and superior PSNR as compared to MATLAB´s adaptive Wiener filter
  • Keywords
    image segmentation; Multiple Compaction Domains; denoising algorithm; segmentation; transform domain thresholding; Additive noise; Additive white noise; Compaction; Computer languages; Gaussian noise; Image segmentation; Mathematical model; Noise reduction; PSNR; Wiener filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    0-7803-5467-2
  • Type

    conf

  • DOI
    10.1109/ICIP.1999.821633
  • Filename
    821633