Noise removal based on surface approximation of color line

Koichiro Manabe, Takuro Yamaguchi, Masaaki Ikehara

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In a local region of a color image, the color distribution often takes the form of a linear line in the RGB space. We call this property "Color Line". We propose a denoising method based on this property. When the noise is added on an image, the color distribution spreads from Color Line. The denoising is achieved by reducing the spread. In conventional methods, Color Line is assumed to be only a single line, but actual distribution takes various shapes such as a single line, two lines, and a flat surface and so on. In our method, we estimate the distribution in more detail using surface approximation and denoise each patch by reducing the spread depending on the color distribution types. In this way, we can achieve better denoising result than a conventional method.

    Original languageEnglish
    Title of host publication2018 International Workshop on Advanced Image Technology, IWAIT 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-4
    Number of pages4
    ISBN (Electronic)9781538626153
    DOIs
    Publication statusPublished - 2018 May 30
    Event2018 International Workshop on Advanced Image Technology, IWAIT 2018 - Chiang Mai, Thailand
    Duration: 2018 Jan 72018 Jan 9

    Other

    Other2018 International Workshop on Advanced Image Technology, IWAIT 2018
    CountryThailand
    CityChiang Mai
    Period18/1/718/1/9

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Vision and Pattern Recognition
    • Media Technology

    Fingerprint Dive into the research topics of 'Noise removal based on surface approximation of color line'. Together they form a unique fingerprint.

  • Cite this

    Manabe, K., Yamaguchi, T., & Ikehara, M. (2018). Noise removal based on surface approximation of color line. In 2018 International Workshop on Advanced Image Technology, IWAIT 2018 (pp. 1-4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWAIT.2018.8369705