Article citationsMore>>

O. G. Guleryuz, “Nonlinear Approximation Based Image Recovery Using Adaptive Sparse Reconstructions and Iterated Denoising: Part I—Theory,” IEEE Transactions on Image Processing, Vol. 15, No. 3, 2006, pp. 539-554. doi:10.1109/TIP.2005.863057

has been cited by the following article:

• TITLE: Super-Resolution with Multiselective Contourlets

  AUTHORS: Mohamed El Aallaoui, Abdelwahad Gourch

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

  JOURNAL NAME: American Journal of Computational Mathematics, Vol.2 No.4, December 25, 2012

  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.