Single image haze removal with WLS-based edge-preserving smoothing filter

Dubok Park, David K. Han, Hanseok Ko

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

    41 Citations (Scopus)

    Abstract

    Images captured under hazy conditions have low contrast and poor color. This is primarily due to air-light which degrades image quality according to the transmission map. The approach to enhance these hazy images we introduce here is based on the 'Dark-Channel Prior' method with image refinement by the 'Weighted Least Square' based edge-preserving smoothing. Local contrast is further enhanced by multi-scale tone manipulation. The proposed method improves the contrast, color and detail for the entire image domain effectively. In the experiment, we compare the proposed method with conventional methods to validate performance.

    Original languageEnglish
    Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
    Pages2469-2473
    Number of pages5
    DOIs
    Publication statusPublished - 2013 Oct 18
    Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
    Duration: 2013 May 262013 May 31

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    ISSN (Print)1520-6149

    Other

    Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
    Country/TerritoryCanada
    CityVancouver, BC
    Period13/5/2613/5/31

    Keywords

    • Air-light
    • dehazing
    • image smoothing
    • multi-scale tone manipulation
    • transmission map

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

    Fingerprint

    Dive into the research topics of 'Single image haze removal with WLS-based edge-preserving smoothing filter'. Together they form a unique fingerprint.

    Cite this