“…Then, the HR image is generated by fusing all the images together and finally an optional deblurring kernel may be applied to the result. For fusing the scaled LR images, different filters can be used, such as mean and median filters [125], [156], [157], [190], [216], [299], [479], adaptive normalized averaging [167], Adaboost classifier [364], and SVD-based filters [582]. These algorithms have been shown to be much faster than the IBP algorithms [ [58], [74], [115], [116], [124], [125], [156], [157], [226] (the last five are known as shift and add), [167], [176], [190], [299], [319], [364], [397], [479], [544], [546], [582] Non-parametric [418], [419], [426], [439], [514], [560], [563], [617] In [125], [156], [157], [216] it was shown that the median fusion of the LR images when they are registered, is equivalent to the ML estimation of the residual of the imaging model of Eq.…”