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This paper introduces a practical algorithm for super-resolution, the process of reconstructing a high-resolution image from low-resolution input ones. The emphasis of the work is to super-resolve frames from real-world image/video sequences which may contain significant object occlusion or scene changes. As the quality of super-resolved images highly relies on the correctness of image alignment between consecutive frames, the robust optical flow method is used to accurately estimate motion between the image pair. An efficient and reliable scheme is devised to detect and discard incorrect matchings which may degrade the output quality. The usage of elliptical weighted average (EWA) filter is also introduced to model the point spread function (PSF) of acquisition system in order to improve accuracy of the model. A number of complex video sequences are tested to demonstrate the applicability and reliability of the proposed algorithm.