Abstract Image fusion is an advanced image processing, in which mean-value coordinates (MVC) algorithm based on Poisson image is a fast and effective algorithm. However, the algorithm may have unsatisfactory results if the source image and target image have many variations of color on the image boundary and image details. To solve the problem, this paper proposes two optimization methods, preserving color based on geodesic distance and matching details with modified detail layer. To verify the feasibility of the methods, the improved MVC results are compared with the original MVC results by experiments. The comparison results show that the improved approach can achieve better performance in image fusion.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Improved Mean-Value Coordinates Algorithm for Image Fusion

    Fu, C. / Shao, Y. / Deng, L. et al. | British Library Conference Proceedings | 2014


    Fast vector quantization image coding by mean value predictive algorithm

    Wu, Y.-G. / Fan, K.-L. | British Library Online Contents | 2004




    Algorithm of Earth-centered Earth-fixed coordinates to geodetic coordinates

    Yuanxin Wu, / Ping Wang, / Xiaoping Hu, | IEEE | 2003