• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.11-18
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• 1997

Scientific volume visualization addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for looking closely into structures and understanding their complexity and dynamics. In the past several years, a tremendous amount of research and development has been directed toward algorithms and data modeling methods for a scientific data visualization. But there has been very little work on developing a mathematical volume model that feeds this visualization. Especially, in flow visualization, the volume model has long been required as a guidance to display the very large amounts of data resulting from numerical simulations. In this paper, we focus on the mathematical representation of volumetric data sets and the method of extracting meaningful information from the derived volume model. For this purpose, a B-spline volume is extended to a high dimensional trivariate model which is called as a flow visualization model in this paper. Two three-dimensional examples are presented to demonstrate the capabilities of this model.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.286-299
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• 2006

Due to the continuing technical progress in the capabilities of modeling, simulation, and sensor devices, huge volume data with very high resolution are common. In scientific visualization, various interactive real-time techniques on high performance parallel computers to effectively render such large scale volume data sets have been proposed. In this paper, we present a mobile volume visualization system that consists of mobile clients, gateways, and parallel rendering servers. The mobile clients allow to explore the regions of interests adaptively in higher resolution level as well as specify rendering / viewing parameters interactively which are sent to parallel rendering server. The gateways play a role in managing requests / responses between mobile clients and parallel rendering servers for stable services. The parallel rendering servers visualize the specified sub-volume with rendering contexts from clients and then transfer the high quality final images back. This proposed system lets multi-users with PDA simultaneously share commonly interesting parts of huge volume, rendering contexts, and final images through CSCW(Computer Supported Cooperative Work) mode.

• Journal of the Korean Society of Visualization
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• v.1 no.2
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• pp.58-70
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• 2003

Meteorological data contains observation and numerical weather prediction model output data. The computerized analysis and visualization of meteorological data often requires very high computing capability due to the large size and complex structure of the data. Because the meteorological data is frequently formed in multi-variables, 3-dimensional and time-series form, it is very important to visualize and analyze the data in 3D spatial domain in order to get more understanding about the meteorological phenomena. In this research, we developed interactive 3-dimensional visualization techniques for visualizing meteorological data on a PC environment such as volume rendering, iso-surface rendering or stream line. The visualization techniques developed in this research are expected to be effectively used as basic technologies not only for deeper understanding and more exact prediction about meteorological environments but also for scientific and spatial data visualization research in any field from which three dimensional data comes out such as oceanography, earth science, and aeronautical engineering.

• 한국가시화정보학회:학술대회논문집
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• 2002.11a
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• pp.77-80
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• 2002

The recent 3D visualization such as volume rendering, iso-surface rendering or stream line visualization gives more understanding about structures or distribution of data in a space and, moreover, the real-time rendering of a scene enables the animation of time-series data. Because the meteorological data is frequently formed as multi-variables, 3-dimensional and time-series data, the spatial analysis, time-series analysis, vector display, and animation techniques can do important roles to get more understanding about data. In this research, our aim is to develop the 3-dimensional visualization techniques for meteorological data in the PC environment by using IDL. The visualization technology from :his research will be used as basic technology not only for the deeper understanding and the more exact prediction about meteorological environments but also for the scientific and spatial data visualization research in any field from which three-dimensional data comes out such as oceanography, earth science, or aeronautical engineering.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.679-691
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• 2002

Volume visualization is an important subarea of scientific visualization, and is concerned with techniques that are effectively used in generating meaningful and visual information from abstract and complex volume datasets, defined in three- or higher-dimensional space. It has been increasingly important in various fields including meteorology, medical science, and computational fluid dynamics, and so on. On the other hand, virtual reality is a research field focusing on various techniques that aid gaining experiences in virtual worlds with visual, auditory and tactile senses. In this paper, we have developed a visualization system for CAVE, an immersive 3D virtual environment system, which generates stereoscopic images from huge human volume datasets in real-time using an improved volume visualization technique. In order to complement the 3D texture-mapping based volume rendering methods, that easily slow down as data sizes increase, our system utilizes an image-based rendering technique to guarantee real-time performance. The system has been designed to offer a variety of user interface functionality for effective visualization. In this article, we present detailed description on our real-time stereoscopic visualization system, and show how the Visible Korean Human dataset is effectively visualized on CAVE.

• Journal of the Korea Computer Graphics Society
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• v.7 no.2
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• pp.21-28
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• 2001

As a result of the recent explosive growth of scientific data, extremely large volume datasets have become increasingly commonplace. While several texture-based volume rendering algorithms have been proposed, most of them focused on volumes smaller than the hardware's available texture memory. This paper presents a new parallel volume rendering scheme for very large static and time-varying data on a multipipe system architecture. Our scheme subdivides large volumes dynamically into smaller bricks, and assigns them adaptively to graphics pipes to minimize the costs of texture swapping. With the new method, Phong shaded images can be easily created by computing the gradients on the fly and using the color matrix feature of OpenGL. We report experimental results on an SGI Onyx2 for the various large datasets.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.87-94
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• 2017

Due to improvements in the capabilities of commercial game engines, there are increasing instances of applying game engines to scientific visualization applications. This study describes a case of creating a virtual reality application that visualizes medical volume data based on the Unity3D game engine. When using a game engine, there is an advantage that various functions required for an application are basically provided, such as depth sorting of translucent objects or virtual reality hardware support. On the other hand, there is a restriction that the structure of the application program should be modified to suit the characteristics of the game engine. This paper describes a method for visualizing medical volume data using the structure of a game engine. As a result, we were able to create a virtual reality scene that consisted of surface data and medical volume data fragments together. And we confirmed the possibility of game engine as a future medical simulation production tool.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.639-646
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• 2006

Data compression technologies enable us to store and transfer large amount of data efficiently, and become more and more important due to increasing data size and the network traffic. Moreover, as a result of the increase of computing power, volumetric data produced from various applied science and engineering fields has been getting much larger. In this Paper, we present a volume compression scheme which exploits Daubeches wavelet transform. The proposed scheme basically supports lossy compression for 3D volume data, and provides unit-wise random accessibility. Since our scheme shows far lower error rates than the previous compression methods based on Haar filter, it could be used well for interactive visualization applications as well as large volume data compression requiring image fidelity.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.982-987
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• 2007

The necessity of data compression scheme for volume data has been increased because of the increase of data capacity and the amount of network uses. Now we have various kinds of compression schemes, and we can choose one of them depending on the data types, application fields, the preferences, etc. However, the capacity of data which is produced by application scientists has been excessively increased, and the format of most scientific data is 3D volume. For 2D image or 3D moving pictures, many kinds of standards are established and widely used, but for 3D volume data, specially time-varying volume data, it is very difficult to find any applicable compression schemes. In this paper, we present a compression scheme for encoding time-varying volume data. This scheme is aimed to encoding time-varying volume data for visualization. This scheme uses MPEG's I- and P-frame concept for raising compression ratio. Also, it transforms volume data using Daubechies D4 filter before encoding, so that the image quality is better than other wavelet-based compression schemes. This encoding scheme encodes time-varying volume data composed of single precision floating-point data. In addition, this scheme provides the random reconstruction accessibility for an unit, and can be used for compressing large time-varying volume data using correlation between frames while preserving image qualities.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.360-370
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• 2004

Adaptive mesh refinement(AMR) is one of the popular computational simulation techniques used in various scientific and engineering fields. Although AMR data is organized in a hierarchical multi-resolution data structure, traditional volume visualization algorithms such as ray-casting and splatting cannot handle the form without converting it to a sophisticated data structure. In this paper, we present a hierarchical multi-resolution splatting technique using k-d trees and octrees for AMR data that is suitable for implementation on the latest consumer PC graphics hardware. We describe a graphical user interface to set transfer function and viewing / rendering parameters interactively. Experimental results obtained on a general purpose PC equipped with an nVIDIA GeForce3 card are presented to demonstrate that the proposed techniques can interactively render AMR data(over 20 frames per second). Our scheme can easily be applied to parallel rendering of time-varying AMR data.