• DocumentCode
    2133609
  • Title

    X-ray image enhancement based on fuzzy sure entropy in LabVIEW

  • Author

    Ce Li ; Yannan Zhou ; Chengsu Ouyang ; Lihua Tian

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Tech, Lanzhou, China
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    395
  • Lastpage
    398
  • Abstract
    Image enhancement is an important problem in image processing and image analysis, especially for low quality X-ray images with both low-illumination and low-contrast. This paper proposes a novel X-ray image enhancement method, which utilizes the maximum fuzzy sure entropy, fuzzy c-partition, and involutive fuzzy complements. In our proposed method, an image is partitioned into dark part and bright part by fuzzy c-partition and the involutive fuzzy complements are obtained, then the exhausted search approach is used to attain the optimal pair and based on the maximum fuzzy sure entropy. In a LabVIEW system platform, many X-ray images have been experimented by the proposed method, and the comparisons of those experimental results show that the proposed scheme has better performance over the traditional algorithms.
  • Keywords
    X-ray imaging; entropy; fuzzy set theory; image enhancement; medical image processing; LabVIEW; X-ray image enhancement; fuzzy c-partition; image analysis; involutive fuzzy complements; low quality X-ray images; low-contrast; low-illumination; maximum fuzzy sure entropy; Fuzzy set theory; Image enhencement; LabVIEW; Shannon entropy; X-ray image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-1183-0
  • Type

    conf

  • DOI
    10.1109/BMEI.2012.6513007
  • Filename
    6513007