Computer Generated Diamond Light Performance Images

Diamond light performance images come in the form of actual photos as well as computer generated images. Learn the distinctions and benefits in this comprehensive article by Whiteflash.

Click below to navigate to a specific section of this article:

• What are computer generated light performance images?
• How are computer generated images produced?
• What kinds of computer generated images are available?
• AGS and DiamCalc computer generated images
• Advanced Light Performance Images on an AGSL Report
• How can you tell the difference between computer generated and actual light performance images?
• Benefits of Computer Generated images
• Actual images vs Computer Generated

Diamond light performance imaging is accomplished by both actual photography of the diamond and by computer simulation based on the attributes of the diamond. Computer generated (CG) light performance images are, as the name implies, images produced by software programs for the purpose of evaluating and communicating different aspects of a diamond’s cut quality and light handling properties. Two of the most instructive and commonly seen CG images are those emulating ASET and Ideal Scope photos. The images produced in this way are referred to as “photo realistic” images as they closely approach the quality of actual photos. In fact, in many cases it is difficult to tell CG images from actual light performance photos.

In the best case the software analyzes a 3D scan of a diamond taken by a non-contact measuring device such as a Sarine, Ogi, or Helium scanner as its input. This very accurate model of the diamond is then put through the paces by the algorithms written into the software to mathematically calculate the light output of the diamond. Images that are rendered by the software are computer generated images, and are created by mapping all the data points from the ray tracing process. Those that are color coded for specifying special aspects of light performance (such as ASET) are therefore also referred to as light maps.

In the absence of an actual scan of a diamond, the basic parameters can be set to the values from a diamond report such as a GIA certificate, or set to any parameters that might be interesting to evaluate for research purposes. If analyzed without an actual scan, the software will assume perfect optical precision (3D symmetry) resulting in images that reflect the basic proportions but that are perfectly symmetrical, which is rarely the case in the real world. If analyzed by inputting values from a GIA report, the computer generated images will also be imprecise because of the averaging and rounding of those values. The accuracy of the computer generated images is therefore much greater if the starting point is an actual 3D scan.

Computer generated images are “renderings” (photo realistic images) that are mapped out mathematically by specialized software programs. Because the physics of light is constant, it is possible to calculate the exact behavior of light rays illuminating a diamond. Those rays can be traced backwards and forwards from the light source to the eye of an observer. Depending on the kind of image being created and its purpose, the light can be mapped in different ways to convey specific information. ASET maps, for example, are color coded to indicate the angular ranges from which the light is entering the diamond and is being returned to the eye of an observer. Other maps can be generated to indicate things about a diamond such as areas of a diamond where the potential of fire is greatest. Generating scintillation maps are also possible, informing about the type of sparkle effects the diamond can produce.

Because the structured mathematical environment is precise and consistent, any number of optical properties can be illustrated by designing light maps for a specific purpose. Color coding is used to enable us to judge these diamond properties at a glance.

There are a great variety of CG images possible, but only a few are available to any significant degree. There are wire frames, fire maps, scintillation maps, animated videos of diamonds in different lighting environments, and of course, ASET and Ideal Scope CG images. The latter two are the most commonly seen, as they arguably contain the most actionable information and are the easiest to deploy.

The two most notable software programs used to produce CG images are those developed by Octonus at Moscow State University, and the program at the heart of the American Gem Society Laboratories (AGSL) light performance cut grading system. The MSU software is DiamCalc which preceded the development of the AGS system. In fact, AGS researchers studied and learned from DiamCalc in the process of developing their own light performance grading system.

The AGS not only studied light behavior with sophisticated ray tracing technology, but also quantified the fundamental components of light performance and developed metrics for grading the cut of a diamond based upon performance. The beauty of the AGS approach is that it can be applied to any shape diamond. The classic round brilliant was the first cut grade to be developed by AGSL, and subsequently princess, oval, emerald cut, and certain cushion cuts have been developed. Since every cut has a different set of attributes that make them desirable, different metrics have to be carefully developed for each shape.

As modern software programs give cutters greater ability to develop new and interesting facet designs, the AGS system can be adapted to provide a scientific basis for grading their cut quality. As information technology has made understanding the importance of cut quality accessible to a new generation of consumers, light performance grading has become much more important to the diamond market.

An AGSL Platinum diamond report contains one or more ASET light maps, depending on the request of the submitting party. These are computer generated images rendered by the AGS Light Performance ray tracing system from the actual 3D model of the diamond. The default light map is the standard face up ASET view. A dual light map report has an additional ASET from pavilion view, the sole purpose of which is to show the precision of the cut. Arrows are seen from the standard view and hearts patterns can be evaluated from the pavilion view, providing an intuitive way to judge the level of optical symmetry. Another light map available on Advanced ASET reports is a face up view rendered at a 40 degree cone of obscuration. In ASET the light blocked by a viewer’s head upon close observation is known as obscuration and is mapped as blue on ASET. So the advanced ASET shows how much light is obscured by closer than normal viewing or viewing by someone with big hair or a hat on. The purpose of this map is to illustrate an aspect of performance that the grading system takes into account in its ray tracing calculations; a well cut diamond should not go completely dark, even when more light is blocked from the highest angles examination. That is, a well cut diamond should be gathering ample light from across the angular spectrum in the hemisphere.

Computer generated ASET maps on AGS Platinum reports provide additional information about cut precision and the distinct way the diamond is handling light, and are invaluable in validating any other light performance photos or diagnostics that might be provided by a merchant.

It is sometimes difficult to determine whether a given image is an actual photo or has been computer generated. But there are several clues that can help. First, inclusions can show up in actual photos whereas they cannot in computer generated images (more on this topic below). Therefore, if you see inclusions you know you are looking at an actual photo. Second, actual images tend to have more variation in color. For example, an ASET photo is taken in an environment simulating the hemisphere with the Blue section of the spectrum at the highest angle. Photography requires a camera lens at this high point in order to snap the picture, and the blackness of the lens can be seen in some photos merging with the blue. This is a strong clue that you are looking at an actual photo.

CG Images produced by inputting basic parameters (rather than an actual scan of the diamond) will have absolutely perfect symmetry. All the patterns will be exactly the same all around the image. In real life, even with precision cut super ideals you can detect small variations in actual photos. If the symmetry has zero variations, it is almost certainly a computer generated image that was not made from a model of the actual diamond.

Computer generated images give consumers and trade members alike a quick graphical view of the light handling properties of diamonds being evaluated for purchase. At a glance we can see problems such as excessive light leakage, too much or too little contrast, and deficits in optical precision.

One of the HUGE benefits of CG images is the ability to analyze theoretical diamonds and see how changes in proportions and angles change the diamond’s performance. It is no longer necessary to physically cut a whole range of different proportion sets to see the results in performance. A parameter can be easily changed in the software and the new light map evaluated for performance changes. This has been a tremendous benefit to researchers and cutters in developing efficiently and cost effectively the best parameters for achieving different goals. New diamond cut designs can be experimented with and proven in a virtual light ray tracing environment before a single piece of expensive diamond rough ever touches the cutting wheel.

As a shopper it is usually better to have too much information about a product than too little. This is especially true of a product so expensive and important as a gem diamond. So it may seem obvious that having BOTH computer generated images and real light performance photos available to you is highly beneficial when making decisions. But beyond the ‘more is more’ benefit, having both CG and actual photos provides validation that the light performance conveyed by the images is true and accurate.

When looking at an online listing with just one or the other, can you be certain that the light map you are looking at actually represents the stone in question? There may be some clues, especially if the photos are actual. But having both actual and CG images provides cross validation and a much higher degree of certainty about the diamond in question.

As mentioned above, one difference between actual photos and CG images is the presence in the actual photos of inclusions. Of course in a very clean diamonds such as VVS clarities an actual photo will look like the CG images in this respect. But in many cases you can verify the match between an actual light performance image and stone plot on the lab report, as well as actual photos or videos of a given diamond by comparing the inclusions present in each.

As we have learned, a CG image is a rendering made from a 3D scan of the exterior of the diamond and has no way of knowing anything about the internal clarity characteristics of the diamond. The model of a Flawless diamond looks exactly the same to the computer program as the model of an Imperfect diamond if all the dimensions, proportions and measurements are the same.

Much is said about the accuracy of computer generated images and whether they can be relied upon for a true evaluation of light performance. In short, the accuracy is largely a function of the scan itself. If the scan is accurate (within the limits of device tolerances), the computer images will be accurate. Nothing changes within the mathematical and algorithmic construct of the software. It is completely consistent and repeatable within the design of its virtual environment, and not subject to additional deviations because of human or other error. It is however, necessary for the scan to be done very carefully and to be checked for error. Scan quality can be affected by things such as dirt or other material on the diamond, stage or lens of the scanner. In the laboratory, multiple scans are taken to ensure that the scan itself has full fidelity.

Despite this reality, some people are of the opinion that actual light performance photographs are more accurate than computer generated images. But it must be remembered that actual photography is also subject to human error and other variables. Thus, it is always best to have BOTH actual photos and computer generated images as they tend to validate one another. If there is significant discordance between them, it is an indication that something is not nominal.

In addition to static images, computer programs can also produce dynamic animations by piecing thousands of images together. These video renderings are surprisingly realistic and can be very useful in understanding performance aspects of a diamond in motion. In addition to color coded light performance images such as ASET, a photo realistic video of the diamond in different lighting environments can be generated.

As we have seen, actual and CG images both have their pros and cons. Ideally, when shopping for a diamond you have all actionable information available for your evaluation. Unfortunately, this is not usually the case. Computer generated images are more available for a couple of reasons. Foremost is that taking actual photos of diamonds requires that you are in possession of those diamonds. Since most diamonds offered on the internet are “virtual inventory” and are not owned by the merchants selling them, they depend on the manufacturers to provide images. Since the manufacture has the 3D scans from the cutting process, the easiest thing to do is to simply render images in the software. Actual high quality photography takes specialized equipment and expertise, and involves much more time to accomplish.

While having both actual and CG images is clearly optimal, in the absence of actual photos CG images provide important information for the consumer.

Viewing a diamond is by nature a dynamic process in that the diamond, the observer, and even the light source can be in motion. For this reason a rendered video can illustrate aspects of diamond performance that can be expected in the real world in ways that static images cannot quite capture.