Open Access<title>Superresolution images reconstructed from aliased images</title>
Author(s) -
Patrick Vandewalle,
Sabine Süsstrunk,
Martin Vetterli
Publication year - 2003
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.506874
Subject(s) - subpixel rendering , aliasing , computer science , computer vision , artificial intelligence , image resolution , image (mathematics) , anti aliasing , dimension (graph theory) , sub pixel resolution , resolution (logic) , iterative reconstruction , algorithm , image processing , pixel , digital image processing , filter (signal processing) , mathematics , digital signal processing , audio signal processing , pure mathematics , computer hardware , audio signal
In this paper, we present a simple method to almost quadruple the spatial resolution of aliased images. From a set of four low resolution, undersampled and shifted images, a new image is constructed with almost twice the resolution in each dimension. The resulting image is aliasing-free. A small aliasing-free part of the frequency domain of the images is used to compute the exact subpixel shifts. When the relative image positions are known, a higher resolution image can be constructed using the Papoulis-Gerchberg algorithm. The proposed method is tested in a simulation where all simulation parameters are well controlled, and where the resulting image can be compared with its original. The algorithm is also applied to real, noisy images from a digital camera. Both experiments show very good results
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