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CAPTURING GROUND TRUTH SUPER-RESOLUTION DATA

机译：捕获地面真理超分辨率数据

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摘要

Super-resolution (SR) offers an effective approach to boost quality and details of low-resolution (LR) images to obtain high-resolution (HR) images. Despite the theoretical and technical advances in the past decades, it still lacks plausible methodology to evaluate and compare different SR algorithms. The main cause to this problem lies in the missing ground truth data for SR. Unlike in many other computer vision tasks, where existing image datasets can be utilized directly, or with a little extra annotation work, evaluating SR requires that the dataset contain both LR and the corresponding HR ground truth images of the same scene captured at the same time. This work presents a novel prototype camera system to address the aforementioned difficulties of acquiring ground truth SR data. Two identical camera sensors equipped with a wide-angle lens and a telephoto lens respectively, share the same optical axis by placing a beam splitter in the optical path. The back-end program can then trigger their shutters simultaneously and precisely register the region of interests (ROIs) of the LR and HR image pairs in an automated manner free of sub-pixel interpolation. Evaluation results demonstrate the special characteristics of the captured ground truth HR-LR face images compared to the simulated ones. The dataset is made freely available for noncommercial research purposes.
机译：超分辨率（SR）提供了一种有效的方法，以提高质量和低分辨率（LR）图像以获取高分辨率（HR）图像的细节。尽管在过去几十年的理论和技术的进步，但仍缺乏合理的方法来评估和比较不同的SR算法。主要原因这一问题的关键在于为SR缺少地面实况数据。不像许多其他计算机视觉任务，在现有的图像数据集可以直接使用，或者用一些额外的注释工作，评估SR要求数据集包含在同一时间拍摄的同一场景的两个LR和相应的HR地面实况图像。这项工作提出了一种新的原型摄像系统，地址获取地面实况SR数据的上述困难。分别配备有广角镜头和远摄镜头两个相同的相机传感器，通过将分束器在光路中共享相同的光轴上。然后后端程序可以同时触发其百叶窗和精确地登记的LR的利益（投资回报）​​和HR图像对的区域中自由子像素内插的自动化方式。评价结果表明，相比那些模拟捕获的大地真HR-LR脸图像的特殊性。该数据集是由免费提供非商业研究目的。

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