Evaluating and Improving Image Quality of Tiled Displays

Abstract

Tiled displays are created by grouping multiple displays together to form one very large display. These tiled displays are often the only suitable option for displaying very large images but suffer from a grid distortion caused by gaps between each sub-display’s active region. This grid distortion is fundamentally different from other, well-studied, image distortions (e.g., blur, noise, compression) and the impact of these grid distortions has thus far not been studied. This research addresses this lack of attention by investigating the grid distortion’s quality impact and creating perceptual algorithms to reduce this impact. We measure the quality impact of the grid distortion by creating two new image quality assessment (IQA) databases for tiled images. These databases provide significant insight into the unique characteristics of the grid distortion and provide a baseline against which to measure the performance of current IQA metrics. We use these databases to show that current metrics do not adequately reflect the quality impact of the grid distortions, and we create a new metric specifically for tiled images that statistically (with 95% confidence) outperforms current metrics. We improve perceived tiled display image quality by creating new image-correction algorithms based on elements of the human visual system (HVS). These correction techniques modify the perceived quality of the displayed images without directly modifying the static grid distortion. These algorithms are shown, through the use of a third subjective user study, to clearly and consistently improve the perceived quality of tiled images.