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Image expansion by linear filtering is attractive and widely used because of its simplicity and efficiency, and many interpolation methods fall in this category. In this study, we model filtering as linear regression from low- to high-resolution color image patches, and propose a learning-based design method of image expansion filters based on sparse Bayesian estimation. Sparseness is imposed on the...
In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such as Support Vector Machines for Regression (SVR) to improve the performance of current H.264 intra prediction via batch learning. In addition, we only use single Macro Block type and one intra prediction mode with high prediction...
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