LED-based display and lighting systems are growing in popularity because of their flexibility, low cost, and efficiency. Therefore, measuring the color and light output of LEDs and LED-based systems is becoming increasingly important as their performance is compared to, and measured against, traditional technologies.
Inherent performance differences from device to device must also be understood and controlled. In measuring LED and LED-based systems, the choice of measurement technique and the system will be a function of measurement objectives and will probably be adapted to the specific nature of the LEDs.
Measurement objectives include assessing or informing an LED or LED-based system design, characterizing a light source, evaluating the source for acceptance testing or quality control, or altering and controlling performance.
Recommendations and standards regarding the measurement of LEDs are vital guides for what measurement quantities are significant and how they could be measured, particularly when characterizing LEDs for utilization in lighting systems.
A set of indicator quantities will most likely suffice, for the outgoing or incoming quality inspection, simplifying the measurements required. It is vital that the measurement relate to human perception of light and color in every instance.
LEDs have a number of interesting characteristics when compared to other light sources. First, the placement of the LED die in the package can affect the direction that light is output significantly. Second, when LEDs are first turned on they need some time to stabilize.
Thirdly, the output of LEDs will vary, non-linearly, with current. Fourth, they are inherently narrowband light sources so the generation of white light requires some form of color mixing.
Lastly, over time LEDs become less efficient because of electron depletion, and so “age” in use, reducing in brightness over time. When measuring LEDs each one of these factors must be considered.
Figure 1. High resolution measurement of LED light and color output is needed for accurate optical design.
Describing LED Color and Brightness
The performance of LEDs, and light sources generally, can be quantified in terms of the angular distribution of their output power as a function of wavelength. Direct description of output power as a function of wavelength is referred to as radiometric.
This spectral power distribution is weighted according to how the human eye perceives different wavelengths and integrated to provide a photometric (brightness as perceived by the human eye) or colorimetric (perceived color) description in order to describe color and brightness as perceived by the human eye.
The color of a source in a particular direction is described as a color space, CIE 1931 is the most common color space. Color is defined here in terms of XYZ coordinates, or tristimulus values, X, Y, and Z, where the Y coordinate is brightness of the source and the chromaticity parameters are derived from X, Y, and Z.
Often, two other quantities describing the color of a source are useful:
Correlated Color Temperature (CCT) is the first of these. This is technically the color temperature of a black body radiator that matches the source the most. CCT is measured in Kelvin (K). Less technically, lower CCT (<3000 °K) are “warmer” (more yellowish), and higher CCT (>5000 °K) are “cooler” (more bluish).
The color-rendering index (CRI) of a light source is a measure of the accuracy of the color appearance of illuminated objects when compared to illumination by natural (ideal) light. CRI can be established using the spectral measurements of a light source, but CRI as a descriptive quantity is problematic.
It supplies indicative information, but in some cases, can be inaccurate; newer methods for defining CRI are actively being explored. These photometric, radiometric, or colorimetric quantities must be described as a function of angle relative to the source to acquire a complete description of an LED, LED lighting or display system.
Luminous intensity is described in units of candela (cd). Brightness is measured as luminous intensity, which is the weighted (according to human perception) power emitted by a light source in a given direction per unit solid angle.
Luminance is a related quantity, which is the luminous intensity per unit area emitted in a particular direction. The units of luminance are candela per square meter (cd/m2); this is often called a “nit”.
This produces three interesting measurement considerations: first, why measure at all; second, what angular granularity is required; and third, is the source measured as an extended source or a point source?
It can be argued that a theoretical model will be enough if the measurements are performed to characterize a source for modeling purposes. Generally, the potential for error in theoretical understanding and the potential complexity of a light source as a system are enough to make a measurement preferred, as it is a real description of the source.
Possessing the real data specific to a device is necessary as the measurement is the point for inspection, evaluation, or control. A point measurement from one viewing angle or a single integrated measurement will be enough for some applications.
The variation of color and luminance with angle is a vital attribute of the device for the majority of applications, particularly for LEDs given manufacturing variations on where the die is placed in the package. A slight variation can lead to significant change in the distribution.
There are two types of angular measurements: those where the angular data is sampled on a grid and those in which all the desired output light is captured and measured.
In the first instance, the spacing between angular measurements can be established based on the anticipated continuity and rate of change of distribution. Normally, good enough estimates of this can be formed to define a measurement series or technique which will generate good data.
Near and Far-Field Measurements
The source may be treated as a point source for some applications (such as evaluating the brightness of an LED indicator light), but for other applications, like characterizing an LED or LED luminaire for optical design, the source should be treated as an extended source. This means one that has physical extent and so has spatial variation in light output from point to point on the source.
In this instance, the source must be measured in a way that yields this more detailed distribution. Measuring the light source as an extended source yields a near-field model of the source and measuring the light as a point source yields a far-field measurement.
In application, for optical design purposes, the near-field model is used as a ray set. The usefulness and quality of the ray set will be a function of both how the rays are statistically sampled and the number of rays in the set, based on the near-field measurements of the source.
Common statistical sampling techniques range from importance sampling to simple Monte Carlo sampling. Instead of just choosing starting points with equal weighting, importance sampling weights rays according to the brightness of the point on the source where they are emitted.
A near-field model may be extrapolated to a far-field model, but the reverse is not true. The reason for this is that the far-field model is a limiting case of the near-field model with a collapsed light source.
A rule of thumb for the boundary between the far- and near-field regions for optical devices is around 10 times the biggest dimension of the source. This would be a few centimeters for an LED, but for a luminaire this could be tens of meters. The near-field model and the far-field model will give essentially the same results beyond this range.
Imaging Colorimetry as Applied to LEDs
Another measurement issue that should be considered is the requirement for spatial data as opposed to a spot or a single point measurement. Spot colorimeters or spectroradiometers only measure a spot on or near the source, and the “spot” is integrated over some regular area.
As it is not very efficient for measuring displays or sources when spatial information is needed, this could supply some helpful information. Imaging colorimeters, which are scientifically calibrated cameras with CIE match photopic and color filters, overcome these issues to supply the equivalent of millions of simultaneous spotmeter readings on a spatial grid.
A typical imaging colorimeter is made up of an image sensor, colorimetric or photopic filters, and lenses. The selection of the image sensor will depend on the application.
To decrease noise levels, the image sensor may be cooled and temperature controlled. Careful electronic design and regulation of readout speed will also decrease the system noise. The colorimetric or photopic filters are preferably specially designed to enable the system to match the CIE color curves for Red, Green, and Blue.
Usually, the overall system, including the lens is extensively calibrated to remove the effects of any optical aberrations or image sensor variations. While not all of the measurements techniques applied to LEDs and LED-based systems require the use of an imaging colorimeter, often these measurements can be made more extensively or quicker by employing one to capture a number of arrayed measurements at the same time.
When measuring an extended light source, an array of LEDs, or an LED display, this is especially important. In each of these instances the spatial relationships are a key component of the data needed to describe and understand the system.
An imaging colorimeter, which only measures photopic information, is known as an imaging photometer. For ease of description of the numerous measurement techniques imaging colorimeters will be referred to, but an imaging photometer may also be utilized, with obvious limitations.
Measuring LED Devices
Usually, measuring LED die or packaged LEDs is performed in R&D to examine different design choices or to characterize the performance of the LED exhaustively.
Using Source Imaging Goniometers
As seen in Figure 2, source imaging goniometers, are designed to measure the near-field luminance distribution of a light source extremely accurately. While there are multiple physical configurations which are possible, virtually all of them move the imaging colorimeter around the light source and capture the output light distribution at the source from many viewing angles (usually thousands).
Figure 2. Source Imaging Goniometer: With two independent axes of rotation a source imaging goniometer maintains precise positioning between the DUT (device under test) and the imaging colorimeter.
This information may be converted to ray sets on the fly or stored as raw data. Either data representation is considered a near-field model.
Critical attributes describing the physical accuracy of the source imaging goniometer are captured in a parameter which is known as “wobble”, this is the maximum excursion of the focal point of the system from its origin as the system is moved to a number of measuring positions.
This wobble should be no more than a few tens of microns when measuring an LED die, which can be about 0.5 mm across, (i.e., only a few percents of the dimension of the die). When measuring packaged LEDs and any other light source, similar accuracy requirements hold.
The quality of the optical system utilized is another vital attribute. The system should have a sufficiently small field of view to permit enough sensor pixels to map the surface of the light source to observe any relevant fine-scale details on the LED die or device.
The most comprehensive representation of the luminance and color output of LED die and devices as a function of angle are Source Imaging Goniometer near-field models. Generally, these measurements take several hours to complete a single source since a scan is made up of thousands of images.
By compromising on imaging optics, angular resolution, or the allowed error, quicker measurement times are possible, but this is unacceptable for LED die and device characterization. Recent advances in source imaging goniometers incorporate the simultaneous acquisition of spectral data.
Using Integrating Spheres
Integrating spheres supply a way to measure the integrated or total light output of an LED. Depending on the sensors used, spectral, colorimetric, radiometric, or photometric, measurements can be acquired.
Usually, an integrating sphere does not gather angular information relative to any of these quantities. Quite simply, an integrating sphere works by putting the LED into the sphere, reflecting the light around the sphere, and measuring the integrated light at a port on the sphere.
Integrating sphere measurements have the benefit of being extremely quick, and it is easy to change sensors to gather spectral, radiometric, or colorimetric measurements. These measurements can be employed to assess or bin LEDs.
The main limitation is that no angular information is acquired, so LED packages with misaligned die (resulting in a skewed directional output of light from the LED) would not be detected.
Using a Photogoniometer
By using a goniometer to move a colorimeter (or spectroradiometer) relative to the LED device, a photogoniometer measures the far-field distribution of an LED. This has the benefit of enabling multiple measurement devices to be used to vary the information gathered from the scan.
The drawback of the photogoniometer is the amount of time that is needed to make the measurement, plus the complexity of attaining the mechanical accuracy required.
Measuring LED Luminaires
There are several applications that require the measurement of LED luminaires: optical design requiring near-field models of LED lamps, quality control, and illumination measurement. The biggest challenge in measuring luminaires is to have enough space to measure large sources.
Using a Near-Field Imaging Goniometer
Near-field Imaging Goniometers are designed to measure large light sources. Generally, there are some design concessions made when compared to source imaging goniometers, to enable a large source to be manipulated in the view of the imaging colorimeter.
Shown in Figure 3, a typical configuration is made up of an imaging colorimeter and a two-axis goniometer. The light source is rotated through an automated measurement sequence in the view of the imaging colorimeter and the associated software creates a near-field model of the source.
This system enables the spectrum of the LED luminaire to be measured at the same time, and so a spectral distribution as a function of viewing angle can also be generated. This technique enables measurement in a very compact laboratory setup since the imaging colorimeter can measure the LED luminaire from within the near field of the light source.
The resultant near-field model can be utilized for optical design via the LED luminaire. The model can also be extrapolated out to give an illumination distribution on any surface, at any distance. The main drawback of this method is the time that a scan takes, which can be a number of hours, depending on the angular step size required.
Figure 3. Measurement of LED luminaires. By directly measuring light sources from within the near field, a combination of a two-axis goniometer and imaging colorimeter can obtain detailed performance measurement in a compact laboratory space.
Using a Photogoniometer
A photogoniometer, usually bigger than the type employed to measure individual LEDs, can be utilized to measure LED luminaires. The sensor must be in the far-field relative to the light source for the measurement to be accurate, so either the system must be fairly large – requiring a large lab, or a system of mirrors is needed to fold the optical path.
Again, the flexibility of utilizing interchangeable sensors is positive, but an extended amount of time, in addition to sufficient lab space, is necessary for a full measurement sequence.
Using an Imaging Colorimeter
To directly measure the illumination distribution of an LED luminaire, an imaging colorimeter can be utilized. To accomplish this, the light from the luminaire is projected on a surface (whose optical response has been baselined) and the imaging colorimeter is employed to image the beam pattern on the surface.
The result of this is an illumination distribution. This measurement is extremely quick – just a few seconds of imaging time – but needs enough space to set up, as the distance from the LED luminaire to the surface (usually a wall) should be enough for a far-field measurement.
Generally, this technique is the best for quality control if the full illumination distribution is desired for making pass/fail decisions, due to the speed of measurement.
Figure 4. Imaging Colorimeter provides very high resolution 2D spatial measurements of luminance or illuminance distribution.
Measuring LED Arrays and Displays
LED arrays, which may be unrelated as in a grouping of indicator lights or related as in LED clusters forming together a lamp, can usually be measured at the same time to increase overall speed and measurement efficiency.
These arrays can be made up of a few LEDs together, to millions of LEDs in a high-resolution LED video screen. The measurement of the array is performed from one particular viewing angle. Usually this is a direct view normal to the array and luminance and color are measured for every individual LED.
This supplies a comparison between LEDs under the same conditions and enables relevant spatial relationships, like the uniformity of color and luminance over an LED display, to be examined.
This data can be used for characterization or evaluation or, in some applications, for control, once the relationship between LEDs has been measured. As the luminance of LEDs can be modified using PWM (pulse width modulation) or current control, this enables the possibility of altering the performance of the LED array by making adjustments in the power to each individual LED.
This measurement information may be utilized to balance output. This spatial information is vital for LED displays, as performance variations between LEDs result in aberrations in the displayed image.
Whether showing still images or videos, a display must be uniform in brightness and color and has to match a prescribed color gamut. The basic performance parameters that apply to any display technology apply to an LED display.
However, there are several ways that LED displays are special: first, the performance of individual pixels can be controlled (with appropriate electronic design); and second, the displays are modular, making differences between modules extremely obvious. So the same imaging colorimeter measurements which capture the performance of the screen can also be utilized to prescribe how to correct the screen.
Figure 5. LED screen performance measurement. Using an imaging colorimeter allows the simultaneous measurement of the light and color output of tens of thousands of LEDs and their spatial relationships. Application software allows their complex relationships to be readily analyzed.
Using an Imaging Colorimeter
As the measurements are taken on a spatial grid that typically matches the way that images and information are presented on display, an imaging colorimeter is ideal for measuring LED arrays and LED (and other) displays.
The image captured with the imaging colorimeter can be segmented automatically into regions of interest that capture the performance of individual LEDs, LED pixels or LED modules, and so supply performance information on global and local uniformity.
This data can be used for LED displays to quantify pixel and module-level correction coefficients to optimize luminance and color uniformity, and to match a target color gamut. Imaging colorimeters have been utilized to measure and correct LED displays both in manufacturing and infield installations.
Due to the scope of applications that exist for LEDs as indicator lights, in luminaires, in backlights, and displays, there is a comparable breadth of photopic, radiometric, and colorimetric measurement techniques.
These techniques balance measurement time, information content, resolution, and logistics to address the requirements of R&D, manufacturing, and field applications. The most important questions to ask in measuring LEDs or LED-based systems are:
- Is angular data required?
- Is near-field or far-field data required?
- Is an array measurement required?
The measurement options will be determined by the answers to these questions. In several instances, the utilization of an imaging colorimeter is optimal because it can capture a large number of simultaneous, spatially related measurements.
It is also flexible enough to be coupled with goniometric systems or other optics (e.g., the imaging sphere) to quickly measure color and light and distributions with high granularity.
As advances are being made in the design and application of LEDs and LED-based systems, advances are also being made in how imaging colorimeters can be employed to measure them (e.g., by integrating spectral measurements) and enhance their performance (e.g., through the correction of LED video displays)
This information has been sourced, reviewed and adapted from materials provided by Radiant Vision Systems.
For more information on this source, please visit Radiant Vision Systems.