Abstract This paper addresses the problem of super resolution – obtaining a single high-resolution image given a set of low resolution images which are related by small displacements. We employ a reconstruction based approach using MRF-MAP formalism, and use approximate optimization using graph cuts to carry out the reconstruction. We also use the same formalism to investigate high resolution expansions from single images by deconvolution assuming that the point spread function is known. We present a method for the estimation of the point spread function for a given camera. Our results demonstrate that it is possible to obtain super-resolution preserving high frequency details well beyond the predicted limits of magnification.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Super Resolution Using Graph-Cut

    Mudenagudi, U. / Singla, R. / Kalra, P. et al. | British Library Conference Proceedings | 2006


    Robust Super-Resolution

    Zomet, A. / Rav-Acha, A. / Peleg, S. et al. | British Library Conference Proceedings | 2001


    Robust super-resolution

    Zomet, A. / Rav-Acha, A. / Peleg, S. | IEEE | 2001


    Super-Resolution Imaging

    Pillman, B.H. | British Library Online Contents | 2013


    Efficient Image Super-Resolution Using Pixel Attention

    Zhao, Hengyuan / Kong, Xiangtao / He, Jingwen et al. | British Library Conference Proceedings | 2020