We present a novel approach to reference-based super-resolution (RefSR) with
the focus on dual-camera super-resolution (DCSR), which utilizes reference
images for high-quality and high-fidelity results. Our proposed method
generalizes the standard patch-based feature matching with spatial alignment
operations. We further explore the dual-camera super-resolution that is one
promising application of RefSR, and build a dataset that consists of 146 image
pairs from the main and telephoto cameras in a smartphone. To bridge the domain
gaps between real-world images and the training images, we propose a
self-supervised domain adaptation strategy for real-world images. Extensive
experiments on our dataset and a public benchmark demonstrate clear improvement
achieved by our method over state of the art in both quantitative evaluation
and visual comparisons.

该研究提出了一种使用参考图像进行高保真图像超分辨率的新方法，针对双摄像头超分辨率进行了重点研究，其利用空间对齐操作推广了标准的基于补丁的特征匹配方法。进一步探索了 RefSR 的一种有前途的应用：双摄像头超分辨率，并构建了由智能手机主摄像头和长焦摄像头的 146 个图像对组成的数据集。此外，为了弥合现实世界图像和训练图像之间的领域差距，该研究提出了一种自我监督的领域自适应策略。对数据集和公共基准的广泛实验表明，该方法在定量评估和视觉比较方面均显著优于现有最优方法。