Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

Автор: Dmytro Peleshko, Taras Rak, Ivan Izonin

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 12 vol.8, 2016 года.

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The paper describes the image superresolution method with aggregate divergence matrix and automatic detection of crossover. Formulation of the problem, building extreme optimization task and its solution for solving the automation determination of the crossover coefficient is presented. Different ways for building oversampling images algorithms based on the proposed method are shows. Based on practical experiments shows the effectiveness of the procedure of automatically the determination of the crossover coefficient. Experimentally established the effectiveness of the procedures oversampling images at high zoom resolution by the developed method.

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Superresolution, similarity measure, crossover operations, automatic detection, aggregate divergence matrix

Короткий адрес: https://sciup.org/15010879

IDR: 15010879

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