High spatial resolution is necessary for several applications such as visual inspection, and can be achieved using high-resolution image sensors or through image super-resolution (SR) algorithms. Currently, super-resolution algorithms are applied to either single low-resolution images or multiple low-resolution image sequences. In this paper, we propose a hybrid super-resolution (HYSR) framework to generate high-resolution images by combining multi-image super-resolution (MISR) and single-image super-resolution (SISR) to obtain high spatial resolution images. This method comprehensively utilizes sub-pixel-level high-frequency detail information between multiple images and co-occurrence prior of a single image to reconstruct SR images with a larger scale factor than the existing methods. Generally, the HYSR reconstruction results have more satisfactory details and visual quality than the SISR or MISR reconstruction results. A large number of qualitative and quantitive evaluation results demonstrate the effectiveness and superiority of the HYSR method over traditional MISR and SISR methods.
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