We address image estimation from sparse Fourier samples. The problem is formulated as joint estimation of the supports of unknown sparse objects in the image, and pixel values on these supports. The domain and the pixel values are alternately estimated using the level-set method and the conjugate gradient method, respectively. Our level-set evolution shows a unique switching behavior, which stabilizes the level-set evolution. Furthermore, the trade-off between the stability and the speed of evolution can be easily controlled by the number of the conjugate gradient steps, hence removing the re-initialization steps in conventional level set approaches.


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    Title :

    A self-referencing level-set method for image reconstruction from sparse Fourier samples


    Contributors:
    Jong Chul Ye, (author) / Bresler, Y. (author) / Moulin, P. (author)


    Publication date :

    2001-01-01


    Size :

    867658 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    A Self-Referencing Level-Set Method for Image Reconstruction from Sparse Fourier Samples

    Ye, J. / Bresler, Y. / Moulin, P. et al. | British Library Conference Proceedings | 2001


    A Self-Referencing Level-Set Method for Image Reconstruction from Sparse Fourier Samples

    Ye, J. C. / Bresler, Y. / Moulin, P. | British Library Online Contents | 2002



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    Referencing

    Papalambros, Panos Y. | Online Contents | 2011