Paper
12 March 1988 Quantitative Fidelity Criterion For Image Processing Applications
Joseph W. Carl
Author Affiliations +
Proceedings Volume 0850, Optics, Illumination, and Image Sensing for Machine Vision II; (1988) https://doi.org/10.1117/12.942852
Event: Advances in Intelligent Robotics Systems, 1987, Cambridge, CA, United States
Abstract
A psychometrically derived, mean square weighted error criterion is defined that mathematically quantifies the difference between an original gray scale image and some reconstructed version of it. The criterion is mathematically tractable in the same sense as the usual mean square error criterion, but it also, (1) accounts analytically for known differences in human spatial frequency contrast sensitivities over six decades of changing luminance, (2) relates to an alternative explanation of certain visual phenomena (such as brightness constancy and the Weber-Fechner law), (3) leads to a relationship between spatial frequency contrast thresholds in human vision and what rate distortion theory tells us about optimal coding for Gaussian channels, and (4) contributes to providing a means of assessing human performance at tasks that involve imagery. Results of an experiment to relate the new fidelity criterion to the prediction of human performance at a target recognition task are presented. Two signal-to-noise ratios and two luminance levels were tested, and a prediction of the effects of those changes was compared to the measured effects. Note that the mean square criterion predicts no change for changing luminance, but changes occur. The new fidelity criterion predicts the direction human performance took as changes were made, but people did worse than predicted.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joseph W. Carl "Quantitative Fidelity Criterion For Image Processing Applications", Proc. SPIE 0850, Optics, Illumination, and Image Sensing for Machine Vision II, (12 March 1988); https://doi.org/10.1117/12.942852
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Cited by 2 scholarly publications.
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KEYWORDS
Contrast sensitivity

Visualization

Spatial frequencies

Distortion

Visual process modeling

Signal to noise ratio

Visual system

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