High-quality volume rendering using texture mapping hardware

1998 ◽  
Author(s):  
Frank Dachille ◽  
Kevin Kreeger ◽  
Baoquan Chen ◽  
Ingmar Bitter ◽  
Arie Kaufman
Keyword(s):  
Volume Rendering ◽  
Texture Mapping ◽  
High Quality

Rendering and Comparing Research of 3D Julia Sets Based on CPU/GPU

2012 ◽  
Vol 542-543 ◽  
pp. 1434-1437
Author(s):  
Xiao Ping Xiao ◽  
Zi Sheng Li ◽  
Wei Gong
Keyword(s):  
Ray Tracing ◽  
Volume Rendering ◽  
Julia Sets ◽  
Time Algorithm ◽  
High Quality

Aiming at the problem that rendering 3D Julia sets on CPU is slowly, a method of rendering 3D Julia sets on GPU is presented in this paper. After introducing the advantages of GPU and the operations of quaternion, the generating process of 3D Julia sets is discussed in detail. Ray tracing volume rendering algorithm is applied to obtain high quality 3D Julia sets, and escaping time algorithm is used to generate the discreet data of Julia sets, of which normal is estimated according to the original of ray and accelerated by using unbounding sphere algorithm, and the graphics examples are given to illustrate this algorithm. Finally, the factors of affecting rendering speed and refined effect are summarized. The results show that the speed of 3D Julia sets rendering on GPU is much faster than CPU, and the interactivity of rendering process is also enhanced.

Modeling and volume rendering approach of underwater three-dimensional acoustic energy field

2016 ◽  
Vol 07 (03) ◽  
pp. 1650019
Author(s):  
Yanyang Zeng ◽  
Panpan Jia
Keyword(s):  
Real Time ◽  
Volume Rendering ◽  
Underwater Acoustics ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Propagation Model ◽  
Acoustic Energy ◽  
Frame Rate ◽  
Volume Data ◽  
Energy Field

The underwater acoustics is primary and most effective method for underwater object detection and the complex underwater acoustics battlefield environment can be visually described by the three-dimensional (3D) energy field. Through solving the 3D propagation models, the traditional underwater acoustics volume data can be obtained, but it is large amount of calculation. In this paper, a novel modeling approach, which transforms two-dimensional (2D) wave equation into 2D space and optimizes energy loss propagation model, is proposed. In this way, the information for the obtained volume data will not be lost too much. At the same time, it can meet the requirements of data processing for the real-time visualization. In the process of volume rendering, 3D texture mapping methods is used. The experimental results are evaluated on data size and frame rate, showing that our approach outperforms other approaches and the approach can achieve better results in real time and visual effects.

scholarly journals Advanced techniques for high-quality multi-resolution volume rendering

2004 ◽  
Vol 28 (1) ◽  
pp. 51-58 ◽  
Author(s):  
S. Guthe ◽  
W. Strasser
Keyword(s):  
Volume Rendering ◽  
High Quality

Real-time volume rendering of 4D image using 3D texture mapping

2001 ◽  
Author(s):  
Jinwoo Hwang ◽  
June-Sic Kim ◽  
Jae Seok Kim ◽  
In Young Kim ◽  
Sun Il Kim
Keyword(s):  
Real Time ◽  
Volume Rendering ◽  
Texture Mapping ◽  
3D Texture ◽  
3D Texture Mapping

scholarly journals MULTIRESOLUTION RENDERING BASED ON GPGPU COMPUTING

2014 ◽  
pp. 298-307
Author(s):  
Julián Lamas-Rodríguez ◽  
Francisco Argüello ◽  
Dora B. Heras
Keyword(s):  
Volume Rendering ◽  
Texture Mapping ◽  
Gpgpu Computing ◽  
Visualization Process ◽  
Resolution Level ◽  
Data Transfers ◽  
Multiresolution Rendering ◽  
Different Levels

The problem of visualizing large volumetric datasets is appealing for computation on the GPU. Nevertheless, the design of GPU volume rendering solutions must deal with the limited available memory in a graphics card. In this work, we present a system for multiresolution volume rendering which preprocesses the dataset dividing it into bricks and generating a compressed version by applying different levels of compression based on wavelets. The compressed volume is then stored in the GPU memory. For the later visualization process by texture mapping each brick of the volume is decompressed and rendered with a different resolution level depending on its distance to the camera. This approach computes most of the tasks in the GPU, thus minimizing the data transfers among CPU and GPU. We obtain competitive results for volumes of size in the range between 64 and 256.

Hybrid Rendering of Multidimensional Image Data

1997 ◽  
Vol 36 (01) ◽  
pp. 1-10 ◽  
Author(s):  
M. Haubner ◽  
A. Lösch ◽  
F. Eckstein ◽  
M. D. Seemann ◽  
W. van Eimeren ◽  
...  
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Volume Rendering ◽  
Image Interpretation ◽  
Texture Mapping ◽  
Volume Visualization ◽  
Data Representation ◽  
Preoperative Treatment ◽  
Hybrid Rendering ◽  
Functional Relationships

Abstract:The most important rendering methods applied in medical imaging are surface and volume rendering techniques. Each approach has its own advantages and limitations: Fast surface-oriented methods are able to support real-time interaction and manipulation. The underlying representation, however, is dependent on intensive image processing to extract the object surfaces. In contrast, volume visualization is not necessarily based on extensive image processing and interpretation. No data reduction to geometric primitives, such as polygons, is required. Therefore, the process of volume rendering is currently not operating in real time. In order to provide the radiological diagnosis with additional information as well as to enable simulation and preoperative treatment planning we developed a new hybrid rendering method which combines the advantages of surface and volume presentation, and minimizes the limitations of these approaches. We developed a common data representation method for both techniques. A preprocessing module enables the construction of a data volume by interpolation as well as the calculation of object surfaces by semiautomatic image interpretation and surface construction. The hybrid rendering system is based on transparency and texture mapping features. It is embedded in a user-friendly open system which enables the support of new application fields such as virtual reality and stereolithography. The efficiency of our new method is described for 3-D subtraction angiography and the visualization of morpho-functional relationships.

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