Contrast enhancement based on layered difference representation

  • Chulwoo Lee*
  • , Chul Li
  • , Chang-Su Kim
  • *Corresponding author for this work

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

    Abstract

    A novel contrast enhancement algorithm based on the layered difference representation is proposed in this work. We first represent gray-level differences at multiple layers in a tree-like structure. Then, based on the observation that gray-level differences, occurring more frequently in the input image, should be more emphasized in the output image, we solve a constrained optimization problem to derive the transformation function at each layer. Finally, we aggregate the transformation functions at all layers into the overall transformation function. Simulation results demonstrate that the proposed algorithm enhances images efficiently in terms of both objective quality and subjective quality.

    Original languageEnglish
    Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
    Pages965-968
    Number of pages4
    DOIs
    Publication statusPublished - 2012
    Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
    Duration: 2012 Sept 302012 Oct 3

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    ISSN (Print)1522-4880

    Other

    Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
    Country/TerritoryUnited States
    CityLake Buena Vista, FL
    Period12/9/3012/10/3

    Keywords

    • Contrast enhancement
    • and constrained optimization
    • histogram equalization
    • layered difference representation

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Information Systems

    Fingerprint

    Dive into the research topics of 'Contrast enhancement based on layered difference representation'. Together they form a unique fingerprint.

    Cite this