Multiscale visualization of 3D geovirtual environments using view-dependent multi-perspective views

3D geovirtual environments (GeoVEs), such as virtual 3D city models or landscape models, are essential visualization tools for effectively communicating complex spatial information. In this paper, we discuss how these environments can be visualized using multi-perspective projections [10, 13] based on view-dependent global deformations. Multi-perspective projections enable 3D visualization similar to panoramic maps, increasing overview and information density in depictions of 3D GeoVEs. To make multi-perspective views an effective medium, they must adjust to the orientation of the virtual camera controlled by the user and constrained by the environment. Thus, changing multi-perspective camera configurations typically require the user to manually adapt the global deformation — an error prone, non-intuitive, and often time-consuming task. Our main contribution comprises a concept for the automatic and view-dependent interpolation of different global deformation preset configurations (Fig. 1). Applications and systems that implement such view-dependent global deformations, allow users to smoothly and steadily interact with and navigate through multi-perspective 3D GeoVEs

Techniques for GPU-based Color Palette Mapping

This paper presents a GPU-based approach to color quantization by mapping of arbitrary color palettes to input images using Look-Up Tables (LUTs). For it, different types of LUTs, their GPU-based generation, representation, and respective mapping implementations are described and their run-time performance is evaluated and compared

Performance Evaluation and Comparison of Service-based Image Processing based on Software Rendering

This paper presents an approach and performance evaluation of performing service-based image processing using software rendering implemented using Mesa3D. Due to recent advances in cloud computing technology (w.r.t. both, hardware and software) as well as increased demands of image processing and analysis techniques, often within an eco-system of devices, it is feasible to research and quantify the impact of service-based approaches in this domain w.r.t. cost-performance relation. For it, we provide a performance comparison for service-based processing using GPU-accelerated and software rendering

Service-based Processing of Gigapixel Images

With the ongoing improvement of digital cameras and smartphones, more and more people can acquire high-resolution digital images. Due to their size and high performance requirements, such Gigapixel Images (GPIs) areoften challenging to process and explore compared to conventional low resolution images. To address this problem,this paper presents a service-based approach for GPI processing in a device-independent way using cloud-basedprocessing. For it, the concept, design, and implementation of GPI processing functionality into service-basedarchitectures is presented and evaluated with respect to advantages, limitations, and runtime performance