Barco is a global technology company that designs and develops visualization solutions for a variety of selected professional markets. One of these markets is medical imaging, for which Barco develops high-quality displays that help doctors to make the right decisions, thereby saving lives.
LCD technology has been the main display technology in the medical imaging market for quite a few years now. OLED display technology is a new emerging technology with a few promising advantages with respect to LCD technology, such as an increased contrast, a larger color gamut, a wider viewing angle, a faster response time, lower depth and weight and a potential for higher brightness and lower cost. Because of these promising characteristics, OLED display technology will become a competitor for LCD technology in the near future.
However, before OLED display technology can become a competitor for LCD technology in the medical imaging market, a few remaining challenges need to be tackled. One of the main issues that OLED displays currently suffer from is a limited lifetime because of the degradation of the organic material in the individual OLED cells (one for each sub-pixel). This degradation manifests itself as a reduction in the intensity of the light emitted from the different pixels in the display. The rate of this reduction is determined by a multitude of factors of which the OLED cell temperature and the current flowing through the OLED cell are the most important.
Since maintaining a constant display performance throughout the lifetime of a display is one of the most important requirements of a medical display, a solution for this behavior is indispensable. A possible way to achieve this consists of first creating a precise OLED aging model and subsequently deducting an adequate compensation technique from it. A model for OLED aging is currently being developed at Barco. The next step consists of deducting an aging compensation technique from this model. This compensation technique can for example consist of an algorithm that adapts the driving of the OLED display in function of time based on the decrease in luminance estimated by the model. The performance of this model could be further improved by gathering instantaneous measurement data such as the luminance and temperature on one or more locations across the screen.
The student working on this master thesis will participate in a project aiming at developing an aging compensation solution for an OLED display. This will encompass a few different tasks.
A first part of the student’s work consists of studying the OLED aging model developed at Barco and identifying the parameters that determine the aging behavior. A careful study of the modelling results will also provide insights into the nature of the behavior (deterministic versus unpredictable).
The outcome of this study should allow defining the requirements of the aging compensation technique. In case the behavior is deterministic, a forward model could be sufficient. In case the behavior is unpredictable to a certain extent, an additional feedback step including luminance or temperature measurements might be required.
Once the requirements of the aging compensation technique are defined, the actual compensation technique can be designed. This consists e.g. of defining when a correction to the driving levels will be applied, when measurement data will be recorded and what calculations will be made. The solution, including all its calculations, will subsequently be implemented, so that its performance can be verified.
Verification of the compensation technique requires sample input data that simulates typical OLED aging. Such data can be obtained through measurements or by means of the OLED aging model. The compensation technique can subsequently be verified in two ways. One way consists of supplying the (numerical) input data to the compensation algorithm and recording the output. Inspection of this output should allow assessing the performance of the solution. An alternative is to visually verify the performance. This can be achieved by visually simulating (accelerated) OLED aging in a shader environment on a GPU and applying the compensation technique on top of it. Visual inspection of the displayed content would then allow identifying the overall visual performance of the solution.