• DocumentCode
    1797121
  • Title

    Denoising for bio-image sequences via matrix decomposition

  • Author

    Qian Li ; Lei Qi ; Guoqiang Bi ; Weiping Li

  • Author_Institution
    Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2014
  • fDate
    9-13 July 2014
  • Firstpage
    515
  • Lastpage
    519
  • Abstract
    Calcium fluorescence imaging is a useful tool in life sciences for visualization of calcium signal in neuronal networks. During the imaging process, noise is inevitably introduced into the image sequences and affects their usefulness. Therefore, noise reduction is an important image processing task for such bio-images. In this paper, a scheme based on matrix decomposition is proposed to denoise this class of bio-image sequences by exploiting the data characteristics. Experimental results have validated the denoising scheme for the class of bio-image sequences.
  • Keywords
    fluorescence; image denoising; image sequences; matrix decomposition; neural nets; bio-image sequences; calcium fluorescence imaging; calcium signal; denoising; imaging process; life sciences; matrix decomposition; neuronal networks; noise reduction; visualization; Calcium; Imaging; Matrix decomposition; Neurons; Noise; Noise reduction; Transient analysis; bio-image denoising; low-rank; matrix decomposition; sparse; total variation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4799-5401-8
  • Type

    conf

  • DOI
    10.1109/ChinaSIP.2014.6889296
  • Filename
    6889296