Dr. Andrew Watson, Senior Scientist for Vision Research, Ames Research Center, Moffett Field, CA

NTB: Can you take us through a typical day for you? What is your day-to-day work? What are you working on now?

Watson: My day consists largely of sitting in front of a computer screen, developing models and metrics of the kind I’ve described, and testing out their application in various domains. One interesting problem I’m working on currently is the application of a model like the Spatial Standard Observer to the image quality of what I would call “remote viewing systems.”

Two examples of remote viewing systems are surveillance video systems and submarine periscopes. In both of these cases, you are monitoring some activity at some distance, and you’re doing it via an electronic imaging system, which has within it optical components and electronic sensors, digital signal processing, image compression, transmission, and then it has display at the other end, where it’s being viewed by a human observer. What we’re trying to do is use models like the Spatial Standard Observer to characterize that end-to-end process and be able to develop numerical metrics for the quality of the entire system, based on the predicted performance of the human observer in using the system.

For example, if the system is being used to identify boats of various kinds, then we will actually be able to simulate the identification of boats through that imaging system using our vision model, and give it a quality metric based on that performance measure. And another application, it might be “Can you see a gun in that hand of someone in an airport security scenario?” There we’ll be able to actually predict the identifiability of handheld devices using that same model. We’re very excited about that work, and that’s a project that I’m currently working on.

However, just to elaborate on that a little bit, a project like this has many parts, and each one of those parts can take a considerable amount of effort and development to accomplish. One part of the project that I just described involves developing a better model for the optical performance of the human eye. The degree of blur by the eye’s optics, for example, depends on various things such as your age, and how large your pupil is. We’ve developed a mathematical model that can compute your optical performance based on those parameters. That optical component will then go into that larger model of visual identification performance.

NTB: Why is SSO a superior option to previous ones? What have been the weaknesses of earlier display metrology?

Watson: There have been a number of other significant efforts in this area in the last 10-20 years, and I want to acknowledge some really excellent work that’s been done by other folks. One difficulty with those other efforts is they have often been quite complicated. The computational machinery involved, the number of parameters involved, and the sophisticated knowledge of the software that was required in order to complete the calculations was quite daunting. As a result, they were rarely used except in research.

One goal of the Standard Observer was to minimize the number of complicated components, the number of complicated calculations, and to, so far as possible, hide the complexity from the user so that it would be more widely applied in actual, practical situations. I think the use of the Standard Observer in the display industry is an indication that we’ve at least partly succeeded in that effort so far.