Measures of image quality based on sensitivity of edge placement have previously been presented for use in imaging system analysis. Successful applications of these measures have included sharpening filter design, interpolator design, system focal length selection, compression bitrate selection, and phase diversity optical control analysis. These are applications for which the General Image Quality Equation (GIQE) is not recommended. The GIQE is intended only for assessment of optimized system designs, and is not robust in system optimization applications.
The alternative to system optimization by engineering metric methods is optimization by human assessments of simulated system design alternatives, a process which is slow and expensive as well as presenting considerable practical difficulties in validation and reproducibility. A practical approach to system design combines metric evaluation of day-to-day problems for which quick answers are needed, with simulation and human evaluation of overall system performance and larger system tradeoffs. In this combined approach one use of metric analysis is to provide reasonable design alternatives to include in the trade space being explored by analyst assessments.
Analysis of simple parametric studies taken from Optical Engineering is presented here in terms of the metrics, with comparison of results achieved with human analysis against results predicted from engineering metrics.
Kristo Miettinen, Kristo Miettinen,
"Application of image quality metrics to problems in remote sensing system design", Proc. SPIE 5438, Visual Information Processing XIII, (15 July 2004); doi: 10.1117/12.542136; https://doi.org/10.1117/12.542136