A multiresolution model for image interpolation with adaptive filtering

This paper proposes an image interpolation model based on a multiresolution scheme. The method uses two different known image resolutions to establish a mapping between them. The mapping is then used to extrapolate the unknown resolution to produce an expanded image with increased definition and with a mean square reconstruction error lower than for the conventional methods. In other words, details in a high resolution image are implicitly predicted based only on its low-frequency resolutions. A high subjective quality is obtained due to the similar nature of the mappings, which are constructed by means of an adaptive bidimensional FIR filter.