  Multi-frame image super-resolution (MISR) aims to fuse information in
low-resolution (LR) image sequence to compose a high-resolution (HR) one, which
is applied extensively in many areas recently. Different with single image
super-resolution (SISR), sub-pixel transitions between multiple frames
introduce additional information, attaching more significance to fusion
operator to alleviate the ill-posedness of MISR. For reconstruction-based
approaches, the inevitable projection of reconstruction errors from LR space to
HR space is commonly tackled by an interpolation operator, however crude
interpolation may not fit the natural image and generate annoying blurring
artifacts, especially after fusion operator. In this paper, we propose an
end-to-end fast upscaling technique to replace the interpolation operator,
design upscaling filters in LR space for periodic sub-locations respectively
and shuffle the filter results to derive the final reconstruction errors in HR
space. The proposed fast upscaling technique not only reduce the computational
complexity of the upscaling operation by utilizing shuffling operation to avoid
complex operation in HR space, but also realize superior performance with fewer
blurring artifacts. Extensive experimental results demonstrate the
effectiveness and efficiency of the proposed technique, whilst, combining the
proposed technique with bilateral total variation (BTV) regu-larization, the
MISR approach outperforms state-of-the-art methods.
