title: Multi-frame image super resolution based on sparse coding.
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.
authors: School of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku, Tokyo, 169-8555, Japan.
authors: Toshiyuki
authors: T
authors: Kato
authors: Department of Computer Science, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8573, Japan. Electronic address: hinohide@cs.tsukuba.ac.jp.
authors: Hideitsu
authors: H
authors: Hino
authors: School of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku, Tokyo, 169-8555, Japan.
authors: Noboru
authors: N
authors: Murata
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*
keywords: Image super resolution; Multi-frame super-resolution; Sparse coding