Texture Generation for use in Synthetic Scenes

In the process of creating synthetic scenes for use in simulations/ visualizations, texture is used as a surrogate to high spatial definition. For example, if one were to measure the location of every blade of grass and all of the characteristics of each blade of grass in a lawn, then in the process of composing a scene of the lawn, it would be expected that the result would appear real; however, because this process is excruciatingly laborious, various techniques have been devised to place the required details in the scene through the use of texturing. Experience gained during the recent Smart Weapons Operability Enhancement Joint Test and Evaluation (SWOE JT&E) has shown the need for higher fidelity texturing algorithms, and a better parameterization of those that are in use. In this study, four aspects of the problem have been analyzed: texture extraction, texture insertion, texture metrics, and texture creation algorithms. The results of extracting real texture from an image, measuring it with a variety of metrics, and generating similar texture with three different algorithms is mixed. The metric (correlation length) thought to be not very capable as a seed for generating texture (based on experience during the evaluation) seems to produce the best results. And though best, the ability is still lacking. The other two metrics are fractal dimension and several parameters derived from the grey-level co-occurrence matrix. These same metrics can be used to define clutter and to make comparisons between real and synthetic (or artificial) scenes in an objective manner.Army Research Lab White Sands Missile Range Nm is the author of 'Texture Generation for use in Synthetic Scenes', published 1997 under ISBN 9781423580782 and ISBN 1423580788.