In this paper, the problem of segmentation of smooth images has been studied using multiresolution analysis. The approximated image intensity function is modeled as a quadratic polynomial with additive noise within local windows. The analysis has been carried out with the aid of a new orthonormal wavelet basis introduced in this paper. A procedure has been developed to approximate an image at a coarse resolution by dropping the components of the image in such a way that small bumps at finer resolutions are suppressed. An image segmentation scheme is proposed. It performs initial segmentation on a coarse approximation of the image, and then updates the segments of the image at a finer resolution. The proposed algorithm has been tested on a variety of real images such as human faces, natural scenes, and medical images.


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    Title :

    Smooth image segmentation via multiresolution analysis


    Contributors:
    Zhou, Jing (author) / Fang, Xiang (author) / Ghosh, Bijoy K. (author)

    Conference:

    Wavelet Applications in Signal and Image Processing II ; 1994 ; San Diego,CA,United States


    Published in:

    Publication date :

    1994-10-11





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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