• DocumentCode
    734181
  • Title

    Depth enhancement via non-local means filter

  • Author

    Ke Yang ; Yong Dou ; Xiaoyang Chen ; Shaohe Lv ; Peng Qiao

  • Author_Institution
    Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2015
  • fDate
    27-29 March 2015
  • Firstpage
    126
  • Lastpage
    130
  • Abstract
    The depth image captured by a RGB-D camera is noisy and usually misses the values at some pixels, especially around the object boundaries. There are many methods take advantage of the corresponding color images to enhance the depth images. Most of them bring the texture of the color image into the depth image. In this paper, an adaptive double non-local means (ADNLM) method of depth enhancement is proposed. First, ADNLM pre-inpaint the depth image via a color-guided non-local means method; second, a depth-based non-local means method is used to denoise the pre-inpainted depth image. Experiments on the public benchmarks show that, ADNLM can avoid the color texture, and effectively enhance the depth image, especially when there are several large missing regions in the depth image. Also, the performance in terms of PSNR of ADNLM is slightly better than that of the state of the arts.
  • Keywords
    cameras; image colour analysis; image denoising; image enhancement; image filtering; image texture; ADNLM method; PSNR; RGB-D camera; adaptive double nonlocal means method; color image texture; color-guided nonlocal means method; depth image enhancement; depth-based nonlocal means method; nonlocal mean filter; preinpainted depth image denoising; Adaptive filters; Filtering; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (ICACI), 2015 Seventh International Conference on
  • Conference_Location
    Wuyi
  • Print_ISBN
    978-1-4799-7257-9
  • Type

    conf

  • DOI
    10.1109/ICACI.2015.7184762
  • Filename
    7184762