Superresolution images reconstructed from aliased images

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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