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Image Quality

Peak signal-to-noise ratio, structural similarity index (SSIM); no-reference image quality metrics; test chart based quality measurements

Quality metrics provide an objective score of image quality. Full reference algorithms compare the input image against a pristine reference image with no distortion. No-reference algorithms compare statistical features of the input image against a set of features derived from an image database.

Standardized test charts contain visual features, such as slanted edges, gray patches, and color patches. These features enable the measurement of corresponding image quality characteristics, such as sharpness and color accuracy.


immse Mean-squared error
psnrPeak Signal-to-Noise Ratio (PSNR)
ssimStructural Similarity Index (SSIM) for measuring image quality
brisqueBlind/Referenceless Image Spatial Quality Evaluator (BRISQUE) no-reference image quality score
fitbrisqueFit custom model for BRISQUE image quality score
brisqueModelBlind/Referenceless Image Spatial Quality Evaluator (BRISQUE) model
niqeNaturalness Image Quality Evaluator (NIQE) no-reference image quality score
fitniqeFit custom model for NIQE image quality score
niqeModelNaturalness Image Quality Evaluator (NIQE) model
esfrChartImatest® edge spatial frequency response (eSFR) test chart
measureSharpnessMeasure spatial frequency response using Imatest® eSFR chart
measureChromaticAberrationMeasure chromatic aberration at slanted edges using Imatest® eSFR chart
measureColorMeasure color reproduction using Imatest® eSFR chart
measureNoiseMeasure noise using Imatest® eSFR chart
measureIlluminantMeasure scene illuminant using Imatest® eSFR chart
displayChartDisplay Imatest® eSFR chart with overlaid regions of interest
displayColorPatchDisplay visual color reproduction as color patches
plotSFRPlot spatial frequency response of edge
plotChromaticityPlot color reproduction on chromaticity diagram


Quality Metrics

Image Quality Metrics

Image quality metrics provide an objective measure of image quality. Each metric has a different computational complexity and agreement with the human perception of image quality.

Train and Use a No-Reference Quality Assessment Model

Learn how to fit a custom model and how to use the model to compute a no-reference quality score.

Obtain Local Structural Similarity Index

This example shows how to measure the quality of regions of an image when compared to a reference image.

Compare Image Quality at Various Compression Levels

This example creates images at various compression levels, then computes and plots the structural similarity quality metrics at each level.

Test Chart Quality Measurements

Anatomy of an eSFR Chart

An Imatest® eSFR chart has visual features including slanted edges, gray patches, color patches, and registration points, for image quality measurements.

Evaluate Quality Metrics on eSFR Test Chart

This example shows how to measure sharpness, chromatic aberration, color accuracy, noise, and illumination on an Imatest® eSFR test chart.

Correct Colors Using Color Correction Matrix

This example shows how to adjust the colors of an image based on color accuracy measurements on an Imatest® eSFR test chart.

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