Improvement of particle-based volume rendering for visualizing irregular volume data sets
نویسندگان
چکیده
منابع مشابه
Improvement of particle-based volume rendering for visualizing irregular volume data sets
We present a technique for previewing large-scale irregular volume datasets using an improved particle-based volume rendering (PBVR) technique. Volume rendering of irregular grid volume data is considerably more complicated than that of regular grid data, since the sampling and compositing processes, which must be done in visibility order, are not straightforward. In our original PBVR, renderin...
متن کاملParticle-Based Volume Rendering of Unstructured Volume Data
Numerical simulations based on Finite Element Methods such as Computational Fluid Dynamics and Computational Structural Mechanics commonly use unstructured grid data in the form of mesh structures, such as tetrahedral meshes. Scientific visualization is a proven effective technique for extracting meaningful information from these datasets, and an efficient visualization method for unstructured ...
متن کاملMultiresolution Wavelet Based Model for Large Irregular Volume Data Sets
In this paper we propose a wavelet based model for large irregular volume data sets by exploiting a multiresolution model based on semi-regular tetrahedral meshes. In order to generate the multiresolution representation we use a wavelet based approach that allows compression and progressive transmission. Beginning with a semi-regular tetrahedral mesh Г∞(T) and applying the wavelet transform, we...
متن کاملStochastic Particle-Based Volume Rendering
In this paper we propose a particle-based volume rendering approach for unstructured three-dimensional tetrahedral polygon meshes. We stochastically generate millions of particles per second that are projected on the screen in real-time. In contrast to previous rendering techniques of tetrahedral volume meshes, our method does not need a prior depth sorting of geometry. Instead, the rendered im...
متن کاملInteractive Texture-Based Volume Rendering for Large Data Sets
tific computation and simulation. Stateof-the-art simulations of physical systems can generate terabytes to petabytes of time-varying data where a single time step can contain more than a gigabyte of data per variable. As memory sizes continue to increase, the size of data sets will likely increase at a comparably high rate. The key to understanding this data is visualizing the global and local...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computers & Graphics
سال: 2010
ISSN: 0097-8493
DOI: 10.1016/j.cag.2009.12.001