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arXiv · 1907.08926

Scene-and-Process-Dependent Spatial Image Quality Metrics

Edward W. S. Fry·Sophie Triantaphillidou·Robin B. Jenkin·Ralph E. Jacobson·John R. Jarvis
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Abstract

Spatial image quality metrics designed for camera systems generally employ the Modulation Transfer Function (MTF), the Noise Power Spectrum (NPS), and a visual contrast detection model. Prior art indicates that scene-dependent characteristics of non-linear, content-aware image processing are unaccounted for by MTFs and NPSs measured using traditional methods. We present two novel metrics: the log Noise Equivalent Quanta (log NEQ) and Visual log NEQ. They both employ scene-and-process-dependent MTF (SPD-MTF) and NPS (SPD-NPS) measures, which account for signal-transfer and noise scene-dependency, respectively. We also investigate implementing contrast detection and discrimination models that account for scene-dependent visual masking. Also, three leading camera metrics are revised that use the above scene-dependent measures. All metrics are validated by examining correlations with the perceived quality of images produced by simulated camera pipelines. Metric accuracy improved consistently when the SPD-MTFs and SPD-NPSs were implemented. The novel metrics outperformed existing metrics of the same genre.

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Edward W. S. Fry, Sophie Triantaphillidou, Robin B. Jenkin, Ralph E. Jacobson, John R. Jarvis. 2019-07-21. Scene-and-Process-Dependent Spatial Image Quality Metrics. https://arxiv.org/abs/1907.08926

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