• DocumentCode
    248671
  • Title

    Denoising based on non local means for ultrasound images with simultaneous multiple noise distributions

  • Author

    Salvadeo, Denis H. P. ; Bloch, Isabelle ; Tupin, Florence ; Mascarenhas, Nelson D. A. ; Levada, Alexandre L. M. ; Deledalle, Charles-Alban ; Dahdouh, Sonia

  • Author_Institution
    DEMAC, Sao Paulo State Univ., Rio Claro, Brazil
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2699
  • Lastpage
    2703
  • Abstract
    In this paper, an extension of the framework proposed by Deledalle et al. [1] for Non Local Means (NLM) method is proposed. This extension is a general adaptive method to denoise images containing multiple noises. It takes into account a segmentation stage that indicates the noise type of a given pixel in order to select the similarity measure and suitable parameters to perform the denoising task, considering a certain patch on the image. For instance, it has been experimentally observed that fetal 3D ultrasound images are corrupted by different types of noise, depending on the tissue. Finally, the proposed method is applied to denoise these images, showing very good results.
  • Keywords
    image denoising; image segmentation; image denoising; image segmentation; multiple noise distributions; ultrasound images; Equations; Image segmentation; Mathematical model; Noise; Noise measurement; Noise reduction; Ultrasonic imaging; image denoising; multiple noises; non local means; ultrasound image; ultrasound segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025546
  • Filename
    7025546