• DocumentCode
    3272649
  • Title

    Weight optimization for multiple image integration

  • Author

    Matsuoka, Ryo ; Yamauchi, Takashi ; Baba, Toshihiko ; Okuda, Masumi

  • Author_Institution
    Fac. of Environ. Eng., Univ. of Kitakyushu, Kitakyushu, Japan
  • fYear
    2013
  • fDate
    15-18 Sept. 2013
  • Firstpage
    795
  • Lastpage
    799
  • Abstract
    We propose a denoising technique using multiple image integration. When acquiring a dark scene, the detail of the dark area is often deteriorated by sensor noise. A simple image integration inherently has the capability of reducing random noises. In this paper we develop the denoising performance of the multiple image integration by optimizing weight maps. We determine the optimal weight by solving a convex optimization problem. Through some experimental results, we show the weight optimization significantly improves the de-noising performance.
  • Keywords
    convex programming; image denoising; convex optimization problem; dark area; dark scene; denoising technique; multiple image integration; weight map optimization; weight optimization; Dynamic range; Noise reduction; Optimization; PSNR; TV; Convex Optimization; Denoising; High Dynamic Range Images; Image Integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2013 20th IEEE International Conference on
  • Conference_Location
    Melbourne, VIC
  • Type

    conf

  • DOI
    10.1109/ICIP.2013.6738164
  • Filename
    6738164