Abstract
Visual metrics can play an important role in the evaluation of novel lighting, rendering, and imaging algorithms. Unfortunately, current metrics only work well for narrow intensity ranges, and do not correlate well with experimental data outside these ranges. To address these issues, we propose a visual metric for predicting visibility (discrimination) and quality (mean-opinion-score). The metric is based on a new visual model for all luminance conditions, which has been derived from new contrast sensitivity measurements. The model is calibrated and validated against several contrast discrimination data sets, and image quality databases (LIVE and TID2008). The visibility metric is shown to provide much…
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Authors
4Topics & keywords
Topics
Keywords
- Luminance
- Metric (unit)
- Computer science
- Contrast (vision)
- Rendering (computer graphics)
- Visibility
- Artificial intelligence
- Image quality
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