Reverse ray tracing from a region of interest backward to the source has long been proposed as an efficient method of determining luminous flux. The idea is to trace rays only from where the final flux needs to be known back to the source, rather than tracing in the forward direction from the source outward to see where the light goes. Once the reverse ray reaches the source, the radiance the equivalent forward ray would have represented is determined and the resulting flux computed. Although reverse ray tracing is conceptually simple, the method critically depends upon an accurate source model in both the near and far field. An overly simplified source model, such as an ideal Lambertian surface substantially detracts from the accuracy and thus benefit of the method. This paper will introduce an improved method of reverse ray tracing that we call Reverse Radiance that avoids assumptions about the source properties. The new method uses measured data from a Source Imaging Goniometer (SIG) that simultaneously measures near and far field luminous data. Incorporating this data into a fast reverse ray tracing integration method yields fast, accurate data for a wide variety of illumination problems.
The color and luminance distributions of large light sources are difficult to measure because of the size of the source and
the physical space required for the measurement. We describe a method for the measurement of large light sources in a
limited space that efficiently overcomes the physical limitations of traditional far-field measurement techniques. This
method uses a calibrated, high dynamic range imaging colorimeter and a goniometric system to move the light source
through an automated measurement sequence in the imaging colorimeter's field-of-view. The measurement is performed
from within the near-field of the light source, enabling a compact measurement set-up. This method generates a detailed
near-field color and luminance distribution model that can be directly converted to ray sets for optical design and that
can be extrapolated to far-field distributions for illumination design. The measurements obtained show excellent
correlation to traditional imaging colorimeter and photogoniometer measurement methods. The near-field goniometer
approach that we describe is broadly applicable to general lighting systems, can be deployed in a compact laboratory
space, and provides full near-field data for optical design and simulation.
Human vision and perception are the ultimate determinants of display quality, however human judgment is variable,
making it difficult to define and apply quantitatively in research or production environments. However, traditional
methods for automated defect detection do not relate directly to human perception - which is especially an issue in
identifying just noticeable differences. Accurately correlating human perceptions of defects with the information that can
be gathered using imaging colorimeters offers an opportunity for objective and repeatable detection and quantification of
such defects. By applying algorithms for just noticeable differences (JND) image analysis, a means of automated,
repeatable, display analysis directly correlated with human perception can be realized. The implementation of this
technique and typical results are presented. Initial application of the JND analysis provides quantitative information that
allows a quantitative grading of display image quality for FPDs and projection displays, supplementing other defect
detection techniques.
Light emitting diodes (LEDs) are being utilized as the light source in increasingly complex and sophisticated products,
including flat panel displays, surgical lamps and even digital projectors. These applications place extreme demands on
LED performance, which, for both the developer and manufacturer, translate into the need to precisely characterize and
control source output, specifically color and luminous intensity distribution characteristics. Unfortunately, the
traditional methods for performing luminous intensity and colorimetric measurements of LEDs suffer from several
significant drawbacks. In particular, spot photometers and radiometers only sample a very limited amount of source
output and operate very slowly. The latter factor can be an important consideration, even in research settings, because
LED output is often not stable over time, especially during warm-up or in the presence of temperature or input power
fluctuations. Thus, a long data acquisition period can make an instrument report spatial output variations that don't
really exist. Now, new instrumentation based on the Imaging Sphere enables rapid, high spatial resolution measurement
of LED color and luminous intensity over an entire hemisphere. This paper reviews the parameters typically utilized to
characterize LEDs, explores Imaging Sphere operation, and compares the results of Imaging Sphere measurements with
highly accurate reference data from a goniophotometer.
Color and luminance uniformity testing of displays is often limited to fewer than ten measurements points on the display surface due to the length of time necessary to make a single point measurement. A CCD-based digital imaging tristimulus colorimeter has been developed which is capable of measuring luminance and chromaticity coordinates at over one million spatial locations in several seconds. The Four-Color Method of colorimeter calibration, recently proposed by NIST, has been employed and found to be superior to single point calibration using Illuminant A. Color and luminance uniformity of a CRT and LCD display were measured using the new digital imaging tristimulus colorimeter and a diode array spectrometer. The data show that chromaticity coordinate and luminance measurements using the CCD-based imaging tristimulus colorimeter compare favorably with the point measurements obtained using a diode array spectrometer over the color gamut of a CRT and LCD display.
As computation speeds have increased dramatically over the last decade, we can now trace enough rays in a short enough time to use ray tracing to predict the performance of an illumination system. The biggest obstacle, however, to accurately model, and thus design, illumination optics is in developing an accurate source model3. In the past, sources were simplistically modeled as very basic geometrical shapes such as points, spheres, or cylinders. Some illumination design software now allows an engineer to create a more complex theoretical model of the source that could include multiple geometrical shapes to more closely approach real source properties. These models, however, are time consuming to create and still fall short of the goal to accurately model the system. Rather than to build up a source model based on a (combination of) geometric shape(s) with some assigned output distribution based on either measured or theoretical data, the authors will demonstrate a new technique for developing and applying source models based on careful, consistent and general measurements. The measurement system consists of a CCD camera mounted on a 2-axis goniometer that allows images of the source to be captured over variable polar and azimuth increments. These source models produce accurate results even when optical surfaces are placed near the source.
Projection lenses are often designed without due consideration to the illumination system. Likewise, most illumination systems are designed to produce a specified intensity and distribution at the LCD surface, without full consideration of the projection optics, and their potential impact to the uniformity at the projection screen. In addition, the effect of the illumination system on the actual MTF of a projection lens can be dramatic (both favorably and unfavorably) compared to the standard MTF calculation which assumes uniformly filling the entrance pupil of the lens. These and other matching issues are discussed, along with ways to analyze and design a well matched system.
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