These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Natural Image Quality Evaluator (NIQE)
Natural image quality evaluator (NIQE) calculates the no-reference image quality score for images that may be distorted or of low perceptual quality. The contribution of this metric is derived from not requiring a known class of image distortions or perception degradations since the measure is not produced with manually-degraded data. Theoretically, this would allow the measure to be more robust to unforeseeable image quality issues. A smaller score indicates better perceptual quality.
NIQE can support the Safety objective in contexts where poor image quality could lead to harmful decisions or outputs, such as in medical diagnostics or autonomous navigation. By quantifying image quality, NIQE helps ensure that AI systems operate on reliable visual data, thereby reducing the risk of harm due to degraded or distorted images. However, this connection is indirect and context-dependent, and NIQE does not address other Trustworthy AI objectives.
About the metric
You can click on the links to see the associated metrics
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