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• W2004351654 abstract "An image super-resolution method from multiple observation of low-resolution images is proposed. The method is based on sub-pixel accuracy block matching for estimating relative displacements of observed images, and sparse signal representation for estimating the corresponding high-resolution image, where correspondence between high- and low-resolution images are modeled by a certain degradation process. Relative displacements of small patches of observed low-resolution images are accurately estimated by a computationally efficient block matching method. The matching scores of the block matching are used to select a subset of low-resolution patches for reconstructing a high-resolution patch, that is, an adaptive selection of informative low-resolution images is realized. The proposed method is shown to perform comparable or superior to conventional super-resolution methods through experiments using various images." @default.
• W2004351654 created "2016-06-24" @default.
• W2004351654 creator A5023633849 @default.
• W2004351654 creator A5031542980 @default.
• W2004351654 creator A5091474846 @default.
• W2004351654 date "2015-06-01" @default.
• W2004351654 modified "2023-10-15" @default.
• W2004351654 title "Multi-frame image super resolution based on sparse coding" @default.
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• W2004351654 doi "https://doi.org/10.1016/j.neunet.2015.02.009" @default.
• W2004351654 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25805366" @default.
• W2004351654 hasPublicationYear "2015" @default.
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