DCT-based high-resolution digital zooming algorithm

In this paper, we propose a digital zooming algorithm to reconstruct a high-resolution image from multiple aliased low-resolution images, which is based on the generalized deconvolution technique. The conventional approaches are based on the discrete Fourier transform (DFT) since the aliasing effect is easily analyzed in the frequency domain. However, the useful solution may not be available in many cases, i.e., the underdetermined cases or the insufficient subpixel information cases. In order to compensate for such ill-posedness, the generalized regularization was adopted in the spatial domain. Furthermore, the usage of the discrete cosine transform (DCT) instead of the DFT leads to the computationally efficient reconstruction algorithm. The validity of the proposed algorithm is both theoretically and experimentally demonstrated in this paper. It is also shown that the artifact caused by inaccurate motion information is reduced by regularization.