Dr. Andrew Watson works on models of human vision and applies them to visual technology. The Founder and Editor in Chief of the Journal of Vision, he is also a Fellow of the Optical Society of America, of the Association for Research in Vision and Ophthalmology, and of the Society for Information Display. Watson received a 2011 Presidential Rank Award from the President of the United States.

NASA Tech Briefs: What is the Spatial Standard Observer (SSO)?

Dr. Watson: For many years we’ve been working on computational models of the early stages of human vision. Part of the purpose of that research is to develop engineering tools that could be used in the design of display technology, compression algorithms, and things of that kind. We have taken a lot of our research and compressed it into a simple engineering tool, the Spatial Standard Observer, which can be used to predict the visibility of artifacts, for example, in a display, or the legibility of information in a display — any case where you have imaging technology that is going to be used by a human observer.

NTB: What role does human test data play in the SSO model? Where is that data coming from?


Watson: Human test data are very important, and the data are of two kinds. One is fundamental data on basic sensitivities of human vision. A lot of that comes from our lab and other labs around the world, where vision scientists are collecting data on how well people can see motion, color, spatial pattern, and temporal change.

The other kind is applied data on questions such as “If we compress this image, can the observer see the artifacts in the image?” Or “If we distort the color in a certain way, will people be sensitive to that distortion?” So we take both those kinds of data and use them to design and calibrate tools like the Spatial Standard Observer.

NTB: Can you take us through a real-world example of how this works, for example, with finding artifacts?

Watson: That’s one of our technologies that has been most widely applied, and in that case, there are about 1 billion flat panel displays manufactured in the world each year; that’s quite remarkable when you think that there are only 6 billion people on Earth. Almost every display needs to be inspected for defects produced during manufacturing. We like to find the defects that are visible to human observers. We don’t really care about the ones that are not visible; the Spatial Standard Observer is uniquely suited to that task because it can tell us when the artifacts are visible. That technology has been licensed to the display industry, and it’s currently in use inspecting, for example, flat panel televisions.

NTB: Can you go through the other applications as well? Aircraft damage? Laser eye surgery?

Watson: Another quite different example is where we’re trying to understand not a piece of imaging technology, but actually the performance of human observers in a visual task. In the case of unmanned aerial vehicles, where there are many efforts to introduce them more widely into the national airspace, there’s great concern about the effects they may have on aviation. One of the issues is the so-called “See and Avoid” rule, where piloted aircraft are generally required to see and avoid other aircraft. Now if there’s no pilot in the unmanned aerial vehicle, how does it see and avoid other aircraft? And under what conditions will it be seen and avoided? So we’ve used the Spatial Standard Observer to actually compute visibility measures for aircraft of various sizes, at various distances, under various meteorological conditions. That can be used to model the introduction of unmanned aerial vehicles into the national airspace and determine under what conditions that would be safe, and under what conditions it will be unsafe.

NTB: What kinds of partnerships are possible with this type of technology?

Watson: The technology is now being used in industry: the display inspection technology that I described earlier. Another example of a different industry that we believe may be able to make use of this technology is laser eye surgery. In that situation, we now have very advanced technology for sculpting the eye in order to reduce the eye’s optical defects.

We don’t have particularly sophisticated ways of predicting the visual outcomes. Another application of the Spatial Standard Observer is to be able to predict from optical measurements of the eye, before surgery and after surgery, what the optical and visual performance of the observer will be. So that’s another industry where we’re hoping that the technology may see some transfer.