Efficient image warping and super-resolution

This paper introduces a new algorithm for enhancing image resolution from an image sequence. The approach we propose herein uses the integrating resampler proposed by M. Chiang and T. Boult (1996) as the underlying resampling algorithm. Moreover, it is a direct method, which is fundamentally different from the iterative, back-projection approaches proposed in previous work. We show that image warping techniques may have a strong impact on the quality of image resolution enhancement. By coupling the degradation model of the imaging system directly into the integrating resampler, we can better approximate the warping characteristics of real sensors, which also highly improve the quality of super-resolution images. Examples of super-resolutions are given for gray-scale images. Evaluations are made by comparing the resulting images and those using bi-linear resampling and back-projection. Results from our experiments show that integrating resampler outperforms traditional bi-linear resampling.