Abstract

AbstractA superresolution process produces a high‐resolution image from a set of low‐resolution images. Reconstruction‐based algorithms to produce the high‐resolution image which minimizes the difference between observed images and images estimated from the high‐resolution image with a camera model have been developed. The reconstruction‐based algorithm requires iterative calculation and has a large calculation cost because reconstruction‐based superresolution is a large‐scale problem. In this paper, a fast algorithm for reconstruction‐based superresolution is proposed. The proposed algorithm reduces the number of observed pixel value estimations from the high‐resolution image, using an average of pixel values in a divided region. The effect of our proposed algorithm is demonstrated with synthetic images and real images. The results show that the proposed algorithm is about 1.4 to 8.5 times faster than conventional algorithms. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(7): 44–52, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20662

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