Efficient super-resolution via image warping
Ming‐Chang Chiang, Terrance E. Boult · Image and Vision Computing · 2000
This paper introduces a new algorithm for enhancing image resolution from an image sequence. The approach we propose herein uses the integrating resampler for warping. The method is a direct computation, which is fundamentally different from the iterative back-projection approaches proposed in previous work. This paper shows 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 significantly improve the quality of super-resolution images. Examples of super-resolutions are given for gray-scale images. Evaluations are made visually by comparing the resulting images and those using bi-linear resampling and back-projection and quantitatively using OCR as a fundamental measure. The paper shows that even when the images are qualitatively similar, quantitative differences appear in machine processing.