Super-Resolution with Multiselective Contourlets

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.

DOI: 10.4236/ajcm.2012.24041                

Abstract

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.

Keywords

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

Conflicts of Interest

The authors declare no conflicts of interest.

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