• DocumentCode
    2833405
  • Title

    Automatic Contrast Enhancement for Low Contrast Images: A Comparison of Recent Histogram Based Techniques

  • Author

    Lakshmanan, Rekha ; Nair, Madhu S. ; Wilscy, M. ; Tatavarti, Rao

  • Author_Institution
    KMEA Eng. Coll., Aluva
  • fYear
    2008
  • fDate
    Aug. 29 2008-Sept. 2 2008
  • Firstpage
    269
  • Lastpage
    276
  • Abstract
    In this paper we compare two recent methods for automatic enhancement of the contrast of the image, based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The histogram based gray level grouping (GLG) method and its variants (after Chen et al., 2006) and the fuzzy logic method (after Hanmandlu and Jha, 2006) are evaluated on three different images (gray scale as well as color) in order to ascertain which of the algorithms are better suited across a variety of images from different sensors and having varying characteristics. Based on the visual quality and the Tenengrad criterion we conclude that the FastHSV variant of the GLG method may be applied for automatic contrast enhancement across a wide variety of images.
  • Keywords
    fuzzy logic; image enhancement; Tenengrad criterion; automatic contrast enhancement; fuzzy logic; histogram based gray level grouping; histogram based technique; low contrast images; skewed histogram; uniform histogram; visual quality; Adaptive equalizers; Background noise; Computer science; Educational institutions; Fuzzy logic; Histograms; Image enhancement; Image sensors; Pixel; Sensor phenomena and characterization; Contrast enhancement; color images; entropy; fuzzy; gray-level grouping; histogram;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2008. ICCSIT '08. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3308-7
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2008.16
  • Filename
    4624874