Multicolor edge function computation

Simon Magarill; Ed English; Boris Ardashnikov

doi:10.1117/12.615290

18 August 2005 Multicolor edge function computation

Simon Magarill, Ed English, Boris Ardashnikov

Proceedings Volume 5867, Optical Modeling and Performance Predictions II; 586703 (2005) https://doi.org/10.1117/12.615290
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

We consider the problem of enhanced analyses to predict/visualize the level of color correction in projection lenses. Modern optical science describes all aspects of chromatic aberrations; however on the projection screen we can see not individual aberrations, but the cumulative effect of light propagation through the system. For example, a combination of spherochromatism and lateral color can create a result that is difficult to visualize. The purpose of this work is to fill the gap between aberration theory and image quality as it can be observed on the screen. One of the important parameters of image quality in the projection industry is the coloration of the border between wide black and white areas on the screen. We developed a computer model for full color image analyses. The output of such modeling is the edge function for individual (up to five) wavelengths or superposition of monochromatic edge functions with chosen waiting factors. It can be presented in graphical and color-coded formats. Basically, the computed superimposed edge function corresponds to what can be seen on the screen. The software supports calculations for a nominal system and for a disturbed system when any possible mechanical error is introduced. Nominal system analysis is useful at the stage of optical design evaluation. Analysis of a disturbed system is a very important instrument for the study of opto-mechanical sensitivity and optimization of the mechanical structure of the lens assembly.

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Simon Magarill, Ed English, and Boris Ardashnikov "Multicolor edge function computation", Proc. SPIE 5867, Optical Modeling and Performance Predictions II, 586703 (18 August 2005); https://doi.org/10.1117/12.615290

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KEYWORDS

Image quality

Visualization

CRTs

Software development

Image analysis

Lenses

Light emitting diodes

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