We introduce a class of inverse problem estimators computed by mixing adaptively a family of linear estimators corresponding to different priors. Sparse mixing weights are calcula...
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
Multiframe super-resolution (SR) reconstruction of small moving objects against a cluttered background is difficult for two reasons: a small object consists completely of "mix...
Adam W. M. van Eekeren, Klamer Schutte, Lucas J. v...
We present an analysis and algorithm for the problem of super-resolution imaging, that is the reconstruction of HR (high-resolution) images from a sequence of LR (lowresolution) im...
Super-resolution image zooming is possible when the image has some geometric regularity. We introduce a general class of non-linear inverse estimators, which combines linear estima...