Sparsity averaging for radio-interferometric imaging
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I. Introduction Wavelets are the result of collective efforts that recognized common threads between ideas and concepts that had been independently developed and investigated by distinct research communities. They provide a unifying framework for decompos ...
A sparse classifier is guaranteed to generalize better than a denser one, given they perform identical on the training set. However, methods like Support Vector Machine, even if they produce relatively sparse models, are known to scale linearly as the numb ...
A Fourier-based approach is presented for the investigation of multilayer superpositions of periodic structures and their moire effects. This approach fully explains the properties of the superposition of periodic layers and of their moire effects, both in ...
In this report we propose a new coding scheme based on the Matching Pursuit algorithm and exploiting some of the new features introduced by H.264 for motion estimation. Main points of this work are the design of a redundant dictionary suitable for coding d ...
To be efficient, data protection algorithms should generally exploit the properties of the media information in the transform domain. In this paper, we will advocate the use of non-linear image approximations using highly redundant dictionaries, for securi ...
