This paper describes a scale evaluation method using nonsubsampled contourlet transform and its application in pavement image enhancement for crack detection. Crack in some scales is much more visible than in others, so a method for scale evaluation is given, and different gains are delivered to each scale for enhancement after scale evaluation. In the first step, noise threshold is computed by noise estimation. And then, sub-groups with 64×64 pixels are divided from the full image at each scale, and group direction variances of these sub-groups are computed for scale evaluation. At last, enhancing process at different scales are taken with gains obtained from scale evaluation. Experiment results show a promising use of the presented method for pavement image enhancement.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Pavement image enhancement based on scale evaluation using nonsubsampled contourlet coefficients


    Contributors:
    He, Li (author) / Qu, Shiru (author) / Zhang, Daqi (author)


    Publication date :

    2009-06-01


    Size :

    4589959 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Pavement Image Enhancement Based on Scale Evaluation Using Nonsubsampled Contourlet Coefficients

    He, L. / Qu, S. / Daqi, Z. | British Library Conference Proceedings | 2009


    Nonsubsampled contourlet transform: construction and application in enhancement

    Jianping Zhou, / Cunha, A.L. / Do, M.N. | IEEE | 2005


    Nonsubsampled Contourlet Transform: Construction and Application in Enhancement

    Zhou, J. / Cunha, A. L. / Do, M. N. | British Library Conference Proceedings | 2005


    Multi-resolution Image Fusion Based on the Nonsubsampled Contourlet Transform

    Tang, L. / Zhao, F. / Zhao, Z.-g. | British Library Online Contents | 2008


    Image fusion with nonsubsampled contourlet transform and sparse representation

    Wang, J. / Peng, J. / Feng, X. et al. | British Library Online Contents | 2013