Author(s)

Mohamed El Aallaoui, Abdelwahad Gourch

Faculté des Sciences Juridiques, économiques et Sociales de Ain Sebaa, Casablanca, Morocco.
Laboratory of Mathematical Engineering (LINMA), Department of Mathematics and Computer Science, Faculty of Sciences, Eljadida, Morocco.

We introduce a new approach to image super-resolution. The idea is to use a simple wavelet-based linear interpolation scheme as our initial estimate of high-resolution image; and to intensify geometric structure in initial estimation with an iterative projection process based on hard-thresholding scheme in a new angular multiselectivity domain. This new domain is defined by combining of laplacian pyramid and angular multiselectivity decomposition, the result is multiselective contourlets which can capture and restore adaptively and slightly better geometric structure of image. The experimental results demonstrate the effectiveness of the proposed approach.

Super-Resolution; Laplacian Pyramid; Angular Multiselectivity; Multiselective Contourlets; Anti-Aliasing Filer; Sparsity Constraint; Iterative Projection

M. Aallaoui and A. Gourch, "Super-Resolution with Multiselective Contourlets," American Journal of Computational Mathematics, Vol. 2 No. 4, 2012, pp. 302-311. doi: 10.4236/ajcm.2012.24041.