Sanghun Park

Wavelet-Based 3D Compression Scheme for Interactive Visualization of Very Large Volume Data

Interactive visualization of very large volume data has been recognized as a task requiring great effort in a variety of science and engineering fields. In particular, such data usually places considerable demands on run‐time memory space. In this paper, we present an effective 3D compression scheme for interactive visualization of very large volume data, that exploits the power of wavelet theory. In designing our method, we have compromised between two important factors: high compression ratio and fast run‐time random access ability. Our experimental results on the Visual Human data sets show that our method achieves fairly good compression ratios. In addition, it minimizes the overhead caused during run‐time reconstruction of voxel values. This 3D compression scheme will be useful in developing many interactive visualization systems for huge volume data, especially when they are based on personal computers or workstations with limited memory.

3D RGB image compression for interactive applications

This paper presents a new 3D RGB image compression scheme designed for interactive real-time applications. In designing our compression method, we have compromised between two important goals: high compression ratio and fast random access ability, and have tried to minimize the overhead caused during run-time reconstruction. Our compression technique is suitable for applications wherein data are accessed in a somewhat unpredictable fashion, and real-time performance of decompression is necessary. The experimental results on three different kinds of 3D images from medical imaging, image-based rendering, and solid texture mapping suggest that the compression method can be used effectively in developing real-time applications that must handle large volume data, made of color samples taken in three- or higher-dimensional space.

Mobile collaborative medical display system

Because of recent advances in wireless communication technologies, the world of mobile computing is flourishing with a variety of applications. In this study, we present an integrated architecture for a personal digital assistant (PDA)-based mobile medical display system that supports collaborative work between remote users. We aim to develop a system that enables users in different regions to share a working environment for collaborative visualization with the potential for exploring huge medical datasets. Our system consists of three major components: mobile client, gateway, and parallel rendering server. The mobile client serves as a front end and enables users to choose the visualization and control parameters interactively and cooperatively. The gateway handles requests and responses between mobile clients and the rendering server for efficient communication. Through the gateway, it is possible to share working environments between users, allowing them to work together in computer supported cooperative work (CSCW) mode. Finally, the parallel rendering server is responsible for performing heavy visualization tasks. Our experience indicates that some features currently available to our mobile clients for collaborative scientific visualization are limited due to the poor performance of mobile devices and the low bandwidth of wireless connections. However, as mobile devices and wireless network systems are experiencing considerable elevation in their capabilities, we believe that our methodology will be utilized effectively in building quite responsive, useful mobile collaborative medical systems in the very near future.

Visualization-specific compression of large volume data

When interactive real-time applications are developed with very large volume data, the use of lossy compression is often inevitable. Lossy compression schemes generally encode data without consideration of the purpose of visualization that is actually performed, which often results in inefficient compression. In this paper, we present a new method for classifying voxels according to their importance in visualization, and assigning appropriate weights to them. The associated weight information can be combined with lossy compression schemes to reduce the visual degradation of reconstructed images, resulting in higher compression rates and visual fidelity. Test results demonstrate that the proposed technique improves both the amount of compression and the quality of visualization significantly.

Making 3D textures practical

While 2D texture mapping is one of the most powerful rendering techniques that make 3D objects appear visually interesting, it suffers from visual artifacts produced when 2D image patterns are wrapped onto the surface of objects with arbitrary shapes. On the other hand, 3D texture mapping generates highly natural visual effects in which objects appear carved from lumps of materials rather than laminated with thin sheets as in 2D texture mapping. Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirements. In this paper, we present a new effective method for 3D texture mapping designed for real-time rendering of polygonal models. Our scheme attempts to resolve the potential texture memory problem arising from the very large size of 3D images by compressing them using a wavelet-based encoding method. The experimental results on various non-trivial 3D textures and polygonal models show that high compression rates are achieved with few visual artifacts in the rendered image and a small impact on rendering time. The simplicity of our compression-based scheme will make it possible to implement practical 3D texture mapping in software/hardware rendering systems including the real-time 3D graphics APIs like OpenGL and Direct3D.

Case study: Interactive rendering of adaptive mesh refinement data

Adaptive mesh refinement (AMR) is a popular computational simulation technique used in various scientific and engineering fields. Although AMR data is organized in a hierarchical multi-resolution data structure, the 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 NVIDIA GeForce card are presented to demonstrate that the technique can interactively render AMR data (over 20 frames per second). Our scheme can easily be applied to parallel rendering of time-varying AMR data.

Parallel Ray Casting of Visible Human on Distributed Memory Architectures

This paper proposes a new parallel ray-casting scheme for very large volume data on distributed-memory architectures. Our method, based on data compression, attempts to enhance the speedup of parallel rendering by quickly reconstructing data from local memory rather than expensively fetching them from remote memory spaces. Furthermore, it takes the advantages of both object-order and image-order traversal algorithms: It exploits object-space and image-space coherence, respectively, by traversing a min-max octree block-wise and using a runtime quadtree which is maintained dynamically against pixels’ opacity values. Our compression-based parallel volume rendering scheme minimizes communications between processing elements during rendering, hence is also very appropriate for more practical distributed systems, such as clusters of PCs and/or workstations, in which data communications between processors are regarded as quite costly. We report experimental results on a Cray T3E for the Visible Man dataset.

Compression-based ray casting of very large volume data in distributed environments

The paper proposes a novel parallel/distributed ray casting scheme for very large volume data that can be effectively used in distributed environments. Our method, based on data compression, attempts to enhance the rendering speedups by quickly reconstructing voxel data from local memory rather than expensively fetching them from remote memory spaces. Our compression based volume rendering scheme minimizes communications between processing elements during rendering computation, hence it is very appropriate for both distributed memory multiprocessors and PC/workstation clusters, where the relatively high communication costs often hinder efficient parallel/distributed processing. We report experimental results on both a Cray T3E and a PC/workstation cluster for the Visible Man dataset.

Compression-Based 3D Texture Mapping for Real-Time Rendering

While 2D texture mapping is one of the most effective of the rendering techniques that make 3D objects appear visually interesting, it often suffers from visual artifacts produced when 2D image patterns are wrapped onto the surfaces of objects with arbitrary shapes. On the other hand, 3D texture mapping generates highly natural visual effects in which objects appear carved from lumps of materials rather than laminated with thin sheets as in 2D texture mapping. Storing 3D texture images in a table for fast mapping computations, instead of evaluating procedures on the fly, however, has been considered impractical due to the extremely high memory requirement. In this paper, we present a new effective method for 3D texture mapping designed for real-time rendering of polygonal models. Our scheme attempts to resolve the potential texture memory problem by compressing 3D textures using a wavelet-based encoding method. The experimental results on various nontrivial 3D textures and polygonal models show that high compression rates are achieved with few visual artifacts in the rendered images and a small impact on rendering time. The simplicity of our compression-based scheme will make it easy to implement practical 3D texture mapping in software/hardware rendering systems including real-time 3D graphics APIs such as OpenGL and Direct3D.

Visualization of Very Large Oceanography Time-Varying Volume Datasets

This paper presents two visualization techniques suitable for huge oceanography time-varying volume datasets on high-performance graphics work- stations. We first propose an off-line parallel rendering algorithm that merges volume ray-casting and on-the-fly isocontouring. This hybrid technique is quite effective in producing fly-through movies of high resolution. We also describe an interactive rendering algorithm that exploits multi-piped graphics hardware. Through this technique, it is possible to achieve interactive-time frame rates for huge time-varying volume data streams. While both techniques have been origi- nally developed on an SGI visualization system, they can be also ported to com- modity PC cluster environments with great ease.