Dark image enhancement based onpairwise target contrast and multi-scale detail boosting

Youngbae Kim, Yeong Jun Koh, Chulwoo Lee, Sehoon Kim, Chang-Su Kim

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

    68 Citations (Scopus)

    Abstract

    A dark image enhancement algorithm based on the pairwise target contrast and the multi-scale detail boosting is proposed in this work. We first compute the pairwise target contrast between a pair of pixels, which represents the desired gray level difference of the two pixels in the output image. By aggregating the pairwise target contrasts for all pairs of pixels in an image, we formulate a cost function for the enhancement. By minimizing the cost function, we obtain the optimal transformation function and enhance the image. In addition, we propose a multi-scale approach to boost details in the globally enhanced image. Experimental results show that the proposed algorithm enhances the contrast and visibility of dark images more effectively than conventional algorithms.

    Original languageEnglish
    Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
    PublisherIEEE Computer Society
    Pages1404-1408
    Number of pages5
    ISBN (Electronic)9781479983391
    DOIs
    Publication statusPublished - 2015 Dec 9
    EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
    Duration: 2015 Sept 272015 Sept 30

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    Volume2015-December
    ISSN (Print)1522-4880

    Other

    OtherIEEE International Conference on Image Processing, ICIP 2015
    Country/TerritoryCanada
    CityQuebec City
    Period15/9/2715/9/30

    Bibliographical note

    Publisher Copyright:
    © 2015 IEEE.

    Keywords

    • Dark image enhancement
    • backlit image enhancement
    • contrast enhancement
    • multi-scale detail boosting
    • pairwise target contrast

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

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