Super-resolution based on low-resolution warped images
Robert A. Gonsalves, Farbod Khaghani · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
Super-resolution based on sequences of low-resolution images has many applications. Among these is improving the image quality of video images, particularly images of historical interest and images from security cameras. Successive frames have slightly different views, or projections, of the object. Not unlike the methods used in computerized tomography, these projections can be combined to produce an image with better resolution than any of the low-resolution views. We observe that in real images even the simplest objects are warped in successive frames. We estimate the warping parameters of each frame and then estimate the object by iterative deconvolution. This forces an appropriate match between a model for the data and the actual data. We show computer simulations of the method and we show some experimental results.