When designing an optical display product (e.g., display monitor, HUD, AR and VR systems), there is great uncertainty about the required image quality of the display to be acceptable by the user. In our experience, there is a great deal of knowledge and experience in the image quality of certain display products, but this experience is accumulated in large organizations that retain the information internally. These organizations invest many years of research and user experience testing to produce a reliable database for the definition of image quality requirements for optimal display product design.
A company that wants to enter the display market and develop a display product, in most cases, does not have the database, experience and knowledge that are needed to produce accurate specifications for the particular use case of interest.
Product developers don’t have a solid knowledge of the different parameters’ importance and impact on the display product performances. They also don’t know how much weight to associate with each parameter and what requirements to specify. Overkill in some requirements can result in a costly and bulky product and in some cases, the particular parameter may be of low importance or sensitivity to the user. On the other hand, there are important parameters that the user is very sensitive to, so they should be considered and be given significant weight.
For example, sometimes, the resolution of a display system beyond a certain limit will not necessarily result in a significant improvement in the eyes of the user, but will require a more complicated optical design. On the other hand, the color quality and contrast in a highly lit and bright environment can have a much more significant impact on visual image quality and designing a system with higher color purity and contrast can create differentiation from competitors’ products.
Over many years of experience, we came across several products that looked very attractive on paper and showed impressive performances, but when compared to an inferior SPEC product in the same use-case they failed to provide the better value and benefits of display quality in the user’s eyes.
There are 2 main ways to evaluate the weight and value of performance parameters as part of the optical system development process:
1. Build an MVP that aims to demonstrate and characterize the quality of the display. The MVP is used for a carefully planned user experiment where the display can be viewed and the users’ feedback collected and analyzed. This option is relatively time-consuming and requires resources investment for building the MVP demo as well as conducting a user experiment.
2. Virtual Prototype - The required display image quality and many external effects can be simulated using appropriate software tools. Using Synopsys LightTools software, for example, a highly accurate system model can be created, which enables to perform optical simulations based on anthropometric data. This "virtual prototyping” allows to gain valuable information about the user's perspective of the system performance with much lower effort, time and costly resources and in many cases can replace prototyping and user experiments in a very early design stage.
Examples of parameters that can be evaluated by this virtual prototyping process in designing AR \ VR or HUD systems:
• The display color quality with the impact of the outside scene background
• The display contrast, relative to the outside scene background
• Display black level contrast and its effect, relative to the outside scene background
• Ghost and stray light artifacts and their visibility on the outside scene background
• System's pupil position effect on the display quality
• Outside scene obscuration by the systems elements
• Product design and its appearance in different lighting conditions
The next image shows a real HUD display non-imaging simulations made in Light tools (Image courtesy of Synopsys). Many parameters can be seen using this simulation like see-through CR, transmission through the HUD, color quality and uniformity of image symbols, artifacts and parallax of the external view through the HUD combiner.
One example of a highly valuable process that aims to understand the required display system performances for the users’ satisfaction is the analysis of an augmented reality system in view of different outside scene backgrounds. We recommended the following steps for this type of non-imaging simulation:
1. Build different sources that represent possible outside scene background types that can be a part of the users’ environment. For example, for a system to be used by a combat soldier, you can build images that represent a forest, a desert scene or an urban environment. Image construction is done by setting parameters such as ambient brightness (which can be derived from geographical location, time of day and season, for example), environment colors, illumination sources and more. All these parameters can be controlled in LightTools software. In addition, you can set the users’ looking distance and place the environment image at this distance.
2. Build a model of a basic AR System, for example, a combiner-based system including the proper definitions of the optical properties and optical surfaces.
3. Build and define the display source - define appropriate brightness, color, polarization and image contrast.
4. Build a receiver located at the user's eye position that enables to examine the ambient source image and the internal AR system image, the ratio and overlap between the two images.
5. It is possible to change and alter the various parameters, and by doing so simulating the different parameters values, which helps to finalize the appropriate requirements values for the optimal system design.
Such a process of building a virtual prototype can make a significant difference and help in the development of a user-tailored system for the specific targeted use-case, with resources and time savings.
One of our specialties is our unique expertise in this virtual prototyping process and the ability to justify the system requirements based on virtual user-experience simulations of the system before a single element is ordered. This proved to be a very cost-effective and efficient process.