High Dynamic Range for High Fidelity Image Synthesis of Real Scenes

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The computer graphics industry, and in particular those involved with films, games, simulation, virtual reality and military applications, continue to demand more realistic computer-generated images, that is computed images that more accurately match the real scene they are intended to represent. This is particularly challenging when considering images of the natural world, which presents our visual system with a wide range of colours and intensities. In most real scenes, for example, looking from inside a house towards a window, the ratio between the darkest areas (e.g. inside the room) and the brightest area (outside the window), the so-called contrast ratio, could be many thousands to one. A typical computer monitor only has a contrast ratio of about 100:1 and is thus incapable of accurately displaying such scenes.A number of appearance-preserving, or tone-mapping, operators (TMOs) have been developed in order to try achieve a perceptual match between the real-world scene and what is displayed on the computer monitor. However, it has not yet been possible to validate the fidelity of these TMOs thoroughly against the real scenes they are trying to portray. The recent development of novel, high dynamic range (HDR) displays, capable of 75,000:1 contrast ratio now provide the opportunity to compute and display computer-generated images that are perceptually much closer to the real world.This research proposal will use these novel HDR displays to evaluate existing TMOs to see how well they do preserve the appearance of the real scenes, and will use the insights gained to develop new, more accurate TMOs for existing computer monitors and HDR displays. A framework will also be produced that will provide a straightforward, objective way of comparing real and synthetic images. Two applications, which are critically dependent on the realism of computed images, are virtual archaeology and military simulations. When investigating past environments on a computer, failure to produce images that accurately match what the past environment may have looked like, may in fact lead to the archaeologists misinterpreting the past. Similarly, the incorrect display of a military vehicle attempting to camouflage in a certain terrain may lead to detection of the vehicle in the real battlefield scenario. We will use specific examples from archaeology and camouflage to test the results of our research.