Raster image adaptation for mobile devices using profiles

Focusing on digital imagery, this paper introduces a strategy to handle heterogeneous hardware in mobile environments. Constrained system resources of most mobile viewing devices require contents that are tailored to the requirements of the user and the capabilities of the device. Appropriate image adaptation is still an unsolved research question. Due to the complexity of the problem, available solutions are either too resource-intensive or inflexible to be more generally applicable. The proposed approach is based on scalable image compression and progressive refinement as well as data and user profiles. A scalable image is created once and used multiple times for different kinds of devices and user requirements. Profiles available on the server side allow for an image representation that is adapted to the most important resources in mobile computing: screen space, computing power, and the volume of the transmitted data. Options for progressively refining content thereby allow for a fluent viewing experience during adaptation. Due to its flexibility and low complexity, the proposed solution is much more general compared to related approaches. To document the advantages of our approach we provide empirical results obtained in experiments with an implementation of the method.