Yuxuan Wang
ABSTRACT
Images taken in low-light environment often face with low dynamic range or color shift caused by lack of illumination. Although many algorithms have been proposed to enhance these images, not much effort has been made on quality assessment of these enhancement results. In our work, we built a database which contains 30 low-light images (both outdoor and indoor scene included) and enhanced images processed by 11 enhancement algorithms. We conducted a subjective experiment based on this database. We found that no algorithm can behave best with images in all situations. Generally, learning-based methods behave better. Further, we also did objective assessment on the database.
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Index Terms
- Perceptual Evaluation of Low-light Image Enhancement Algorithms
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