Reconstruction of 2-d image primitives or of 3-d volumetric primitives is one of the most common operations
performed by the rendering components of modern visualization systems. Because this operation is often aided by
GPUs, reconstruction is typically restricted to first-order interpolation. With the advent of in situ visualization,
the assumption that rendering algorithms are in general executed on GPUs is however no longer adequate. We
thus propose a framework that provides versatile texture filtering capabilities: up to third-order reconstruction
using various types of cubic filtering and interpolation primitives; cache-optimized algorithms that integrate
seamlessly with GPGPU rendering or with software rendering that was optimized for cache-friendly "Structure
of Array" (SoA) access patterns; a memory management layer (MML) that gracefully hides the complexities
of extra data copies necessary for memory access optimizations such as swizzling, for rendering on GPGPUs,
or for reconstruction schemes that rely on pre-filtered data arrays. We prove the effectiveness of our software
architecture by integrating it into and validating it using the open source direct volume rendering (DVR) software
DeskVOX.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.