Safa Chérigui

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This paper describes new image prediction methods based on neighbor embedding (NE) techniques. Neighbor embedding methods are used here to approximate an input block (the block to be predicted) in the image as a linear combination of <i>K</i> nearest neighbors. However, in order for the decoder to proceed similarly, the <i>K</i> nearest neighbors are found(More)
The paper describes a K-NN search method aided by local learning of subspace mappings for the problem of neighbor-embedding based image Intra prediction. The local learning of subspace mappings relies on multivariate linear regression. The method is used jointly with Locally Linear Embedding (LLE) as well as with a method inspired from Non Local Means (NLM)(More)
Template matching has been shown to outperform the H.264 prediction modes for Intra video coding thanks to better spatial prediction and no additional ancillary data to transmit. The method indeed works well when the template and the block to be predicted are highly correlated, e.g., in homogenous image areas, however, it obviously fails in areas with non(More)
Image prediction methods based on data dimensionality reduction techniques have been introduced in [1]. Although efficient, these methods suffer from limitations when the block to be predicted and its neighborhood (or template) are not correlated, e.g. in non homogenous texture areas. To cope with these limitations, this paper introduces new image(More)
This paper describes a novel image coding scheme based on epitome inpainting. An epitome containing a factorized texture representation of the image is first coded and transmitted. The decoded epitome is then inpainted by propagating its structure and texture with extended H.264 Intra directional prediction modes and advanced neighbor embedding methods. The(More)
This paper addresses the problem of epitome construction for image compression. An optimized epitome construction method is first described, where the epitome and the associated image reconstruction, are both successively performed at full pel and sub-pel accuracy. The resulting complete still image compression scheme is then discussed with details on some(More)
Image prediction methods based on data dimensionality reduction techniques have been recently introduced for still images. These techniques have been proven efficient, especially when used in a H.264 framework. This paper introduces a natural extension of this work from spatial prediction to temporal prediction. Locally Linear Embedding and Optimized(More)
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