Discrete cosine transform based high-resolution image reconstruction considering the inaccurate subpixel motion information

The demand for high-resolution images is gradually increasing, whereas many imaging systems have been designed to enable a certain level of aliasing during image acquisition. In this sense, digital image processing approaches have recently been investigated to reconstruct a high-resolution image from aliased low-resolution images. However, since the subpixel motion information is assumed to be accurate in most conventional approaches, the satisfactory high-resolution image cannot be obtained when the subpixel motion information is inaccurate. Hence, we propose a new algorithm to reduce the distortion in the reconstructed high-resolution image due to the inaccuracy of subpixel motion information. For this purpose, we analyze the effect of inaccurate subpixel motion information on a high-resolution image reconstruction, and model it as zero-mean additive Gaussian errors added respectively to each low-resolution image. To reduce the distortion, we apply the modified multichannel image deconvolution approach to the problem. The validity of the proposed algorithm is demonstrated both theoretically and experimentally.