Task-Oriented Evaluation of Super-Resolution Techniques

Li Tian, Akira Suzuki, Hideki Koike

Abstract: The goal of super-resolution (SR) techniques is to enhance the resolution of low-resolution (LR) images. How to evaluate the performance of an SR algorithm seems to be forgotten when researchers keep producing algorithms. This paper presents a task-oriented method for evaluating SR techniques. Our method includes both objective and subjective measures and is designed from the viewpoint of how SR impacts many essential image processing and vision tasks. We evaluate some state-of-the-art SR algorithms and the results suggest that different SR algorithms should be utilized for different applications. In general, they reflect the consistency and conflict between objective and subjective measures as well as computer vision systems and human vision systems do.