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This paper proposed a new image inpainting method based on morphological component analysis that is capable of filling in holes in overlapping texture and cartoon layers. Firstly, due to rich content and complex color of Tangka image, the imposition of a total variation penalty by conventional model may not be accurate and easy to produce staircase. To improve the performance of sparse-representation-based...
In this paper, we propose a Lasso based framework to generate the sparse total variability supervectors (s-vectors). Rather than the factor analysis framework, which uses a low dimensional Eigenvoice subspace to represent the mean supervector, the proposed Lasso approach utilizes the l1 norm regularized least square estimation to project the mean supervector on a pre-defined dictionary. The number...
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