LMK Sticking Image: Burn-in- & Image-Retention-Messung

This study introduces two proposed Image Sticking evaluation methods from the automotive industry and identifies relevant differences. It further focusses on the importance of precise temporal alignment and outlines the differences between temporal and local non-uniformity corrections as well as grey level dependency. The complete study bases on measured data.

Modern automotive displays may be sensitive to static content, which remains as an undesired effect of either temporary vanishing or being a static ghost image within the refreshed content. Therefore, there is a development of measurement procedures to quantize the degree of image sticking [1- 6]. Different aspects of these methods as the grey level dependencies or the importance of a temporal alignment were considered in [7]. But the mathematically necessary separation of unavoidable initial non-uniformities and the actual image sticking was excluded in that research.
This contribution concentrates on the performance of two selected image sticking evaluation methods [5, 6] from the automotive community and [1] for reference. After briefly introducing the three methods, this contribution focusses on their capability of separating initial non-uniformities from the actual sticking image effect of the target display. Therefore, a mathematical analysis, which is based on a simple but physically motivated sticking image model, is performed. Based on that, an additional non-uniformity correction is proposed. This additional correction has a positive influence on the precision but a negative influence on the measurement time of the fastest measurement method [6]. Thus, we propose a workflow, that decides based on the properties of the DUT whether the correction is necessary or not. All conclusions are supported by simulations and validated using measurement results of a randomly chosen non-uniform automotive LC display.
The aim of this paper is on the one hand to quantize the mathematical influence of the methods and on the other hand to suggest a workflow, which utilizes an existing method and optimizes its application with respect to precision and overall measurement time.

Image Sticking is an undesired display property, which requires time-consuming and expensive testing. This study summarizes some proposed Image Sticking evaluation methods and identifies relevant differences. It derives aspects, which should be considered prior to a time-consuming and potentially irreversible Sticking Image measurement. Further, parameter analysis associated with the Imaging Luminance Measurement Device is briefly outlined.