Single-Image Super-Resolution: A Benchmark

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Authors Chih-Yuan Yang, Chao Ma, Ming-Hsuan Yang
Journal/Conference Name ECCV
Paper Category
Paper Abstract Single-image super-resolution is of great importance for vision applications, and numerous algorithms have been proposed in recent years. Despite the demonstrated success, these results are often generated based on different assumptions using different datasets and metrics. In this paper, we present a systematic benchmark evaluation for state-of-the-art single-image super-resolution algorithms. In addition to quantitative evaluations based on conventional full-reference metrics, human subject studies are carried out to evaluate image quality based on visual perception. The benchmark evaluations demonstrate the performance and limitations of state-of-the-art algorithms which sheds light on future research in single-image super-resolution.
Date of publication 2014
Code Programming Language MATLAB
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