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Multi-frame image super resolution based on sparse coding
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DOI：10.1016/j.neunet.2015.02.009.png)
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Abstract
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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. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Image super resolution
Multi-frame super-resolution
Sparse coding
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