CTDNet: cartoon-texture decomposition-based gray image super-resolution network with multiple degradations
Baoshun Shi,
Wenyuan Xu,
Xiuwei Yang
Abstract:In the case of multiple degradations, current deep-learning-based gray image super-resolution (SR) methods equally process all components in an image, resulting in missing subtle details. To address this issue, we elaborate a cartoon-texture decomposition-based (CTD) module that can automatically decompose an image into a smooth cartoon component and an oscillatory texture component. The CTD module is a plug-and-play prior module that can be applied in solving imaging inverse problems. Specifically, for the SR… Show more
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