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In medical diagnosis, high resolution (HR) images are indispensable for giving more correct decision. The super resolution technique, which can generate HR images from LR images based on machine learning, attracts hot attention recently. However, the conventional learning based SR generally cannot recover high frequency information. In this paper, we integrate a further learning step into the conventional...
Face Hallucination, one of the most famous learning-based image super-resolution techniques for facial images, can reconstruct a high-resolution image using only one low-resolution image. However, some detailed high-frequency components of the reconstructed image cannot be recovered using this method. In addition, the available LR images are sometimes blurred because of object movement or hardware...
Face Hallucination is, one of a learning-based super-resolution technique that can reconstruct a high-resolution image using only one low-resolution image. However, there are often some detailed high-frequency components of the reconstructed image that cannot be recovered using this method. In this study, we proposed a high-frequency compensated face hallucination method for enhancing reconstruction...
Recently, with the development of visual communication and image processing, there is a high demand for high-resolution images such as video surveillance, medical imaging, and so on. Therefore, the super-resolution technology that produces a high-resolution image from a set of shifted, blurred, and decimated versions is actively researched. However, most previously published techniques perform well...
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