论文标题
使用非对流映射将低分辨率图像映射到多个高分辨率图像
Mapping Low-Resolution Images To Multiple High-Resolution Images Using Non-Adversarial Mapping
论文作者
论文摘要
最近已经提出了几种图像超分辨率（SISR）问题的方法。当前方法假设单个低分辨率图像只能产生单个高分辨率图像。此外，所有这些方法都使用通过简单双线性下采样人为生成的低分辨率图像。我们认为，首先，SISR的问题是低分辨率和所有可能的候选高分辨率图像之间的一对多映射问题，我们解决了学习如何实际降级和下样本的高分辨率图像的具有挑战性的任务。为了解决这个问题，我们提出了使用非对抗映射（NAM）技术的SR-NAM。此外，我们提出了一个退化模型，该模型学习如何将高分辨率图像转换为相似于现实拍摄低分辨率照片的低分辨率图像。最后，包括提出的方法以及SR-NAM的弱点的一些定性结果。
Several methods have recently been proposed for the Single Image Super-Resolution (SISR) problem. The current methods assume that a single low-resolution image can only yield a single high-resolution image. In addition, all of these methods use low-resolution images that were artificially generated through simple bilinear down-sampling. We argue that, first and foremost, the problem of SISR is an one-to-many mapping problem between the low-resolution and all possible candidate high-resolution images and we address the challenging task of learning how to realistically degrade and down-sample high-resolution images. To circumvent this problem, we propose SR-NAM which utilizes the Non-Adversarial Mapping (NAM) technique. Furthermore, we propose a degradation model that learns how to transform high-resolution images to low-resolution images that resemble realistically taken low-resolution photos. Finally, some qualitative results for the proposed method along with the weaknesses of SR-NAM are included.
