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This paper aims at how to reconstruct a super-resolution image in a fast speed based on linear kernel regression. We use linear kernel regression to learn a map between the space of high-resolution images and the space of blurred high-resolution images that are the interpolation results obtained from the corresponding low-resolution images, because linear kernel regression is simple and has low computational...
In this paper, a novel approach to single image super-resolution based on the multikernel regression is presented. This approach's core is to learn the map between the space of high-resolution image patches and the space of blurred high-resolution image patches which are the interpolation results generated from the corresponding low-resolution images. Kernel regression based super-resolution approach...
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