• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.169-172
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• 2000

Direct volume rendering has yet been restricted to high-end graphic workstations and special-purpose hardware, due to the large amount of trilinear interpolation, that are necessary to obtain high image quality. In this paper, we implemented the volume rendering techniques using the 2D-texture at the environment of standard PC hardware. In addition, we show how multi-texturing capabilities of modern PC graphics board are enable to volume rendering. Besides using extended OpenGL function, we improved pixel operations and rendering capacity.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.971-981
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• 2006

As shear-warp volume rendering is the fastest rendering method among the software based approaches, image quality is not good as that of other high-quality rendering methods. In this paper, we propose two methods to improve the image quality of shear-warp volume rendering without sacrificing computational efficiency. First, supersampling is performed in intermediate image space. We propose an efficient method to transform between volume and image coordinates at the arbitrary ratio. Second, we utilize pre-integrated rendering technique for shear-warp rendering. We propose new data structure called overlapped min-max map. Using this structure, empty space leaping can be performed so that we can maintain the rendering speed even though pre-integrated rendering is applied. Consequently, shear-warp rendering can generate high-qualify images comparable to those generated by the ray-casting without degrading speed.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.316-324
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• 2007

Maximum Intensity Projection (MIP) identifies patients' anatomical structures from MR or CT data sets. Recently, it becomes possible to generate MIP images with interactive speed by exploiting Graphics Processing Unit (GPU) even in large volume data sets. Generally, volume boundary plane is obliquely crossed with view-aligned texture plane in hardware-texture based volume rendering. Since the ray sampling distance is not increased at volume boundary in volume rendering, the aliasing problem occurs due to data loss. In this paper, we propose an efficient method to overcome this problem by Re-rendering volume boundary planes. Our method improves image quality to make dense distances between samples near volume boundary which is a high frequency area. Since it is only 6 clipping planes are additionally needed for Re-rendering, high quality rendering can be performed without sacrificing computational efficiency. Furthermore, our method couldbe applied to Minimum Intensity Projection (MinIP) volume rendering.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.158-167
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• 2015

This study presents a new method to improve the speed of high quality volume rendering. We improve the speed of ambient occlusion which is one of the global illumination techniques used in traditional volume visualization. Calculating ambient occlusion takes much time because it determines an illumination value of a sample by integrating opacities of nearby samples. This study proposes an improved method for this by using local statistics such as averages and standard deviations. We calculate local statistics for each volume block, a set of nearby samples, in pre-processing time. In the rendering process, we efficiently determine the illumination value by assuming the density distribution as a normal distribution. As the results, we can generate high quality images that combine ambient occlusion illumination with local illumination in real time.

• 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 Korea Computer Graphics Society
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• v.24 no.2
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• pp.29-40
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• 2018

Direct volume rendering (DVR) is a commonly used method to visualize inner structures in 3D volumetric datasets. However, conventional volume rendering on a 2D display lacks depth perception due to dimensionality reduction caused by ray casting. In this work, we investigate how emerging Virtual Reality (VR) can improve the usability of direct volume rendering. We developed real-time high-resolution DVR system in virtual reality, and measures the usefulness of volume rendering with improved depth perception via a user study conducted by 38 participants. The result indicates that virtual reality significantly improves the usability of DVR by allowing better depth perception.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.276-284
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• 2022

In this paper, we implemented cloud rendering using WebRTC for high-quality AR and VR services. Cloud rendering is an applied technology of cloud computing. It efficiently handles the rendering of large volumes of 3D content. The conventional VR and AR service is a method of downloading 3D content. The download time is delayed as the 3D content capacity increases. Cloud rendering is a streaming method according to the user's point of view. Therefore, stable service is possible regardless of the 3D content capacity. In this paper, we implemented cloud rendering using WebRTC and analyzed its performance. We compared latency of 100MB, 300MB, and 500MB 3D AR content in 100Mbps and 300Mbps internet environments. As a result of the analysis, cloud rendering showed stable latency regardless of data volume. On the other hand, the conventional method showed an increase in latency as the data volume increased. The results of this paper quantitatively evaluate the stability of cloud rendering. This is expected to contribute to high-quality VR and AR services

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.852-861
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• 2013

When users use medical volume rendering applications, selecting specific region of volume data and observing the region by magnification is a common process.As the wood-grain artifact is arise from the magnified image, the jittered sampling technique has been used to remove the problem. However, the jittered sampling leads to some noise along the volume edge. In this research, we reveal the reason of the noise, and present a solution. To remove the wood-grain artifact without the noise, we propose the empty space jittering and the sampling alignment method. Using these methods, we can produce high quality volume rendering images without noticeable time consuming.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.191-196
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• 2009

Volume rendering is a method which extracts meaningful information from volume data and visualizes those information. In general, since the size of volume data gets larger, it is very important to devise acceleration methods for interactive rendering speed. Min-max octree is data structure for high-speed volume rendering, however, its creation time becomes long as the data size increases. In this paper, we propose acceleration method of min-max octree generation using CUDA. Firstly, we convert one-dimensional array from volume data using space filling curve. Then we make min-max octree structures from the sequential array and apply them to acceleration of volume ray casting.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.512-520
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• 2009

Maximum intensity projection (MIP) is a volume rendering method which extracts maximum values along the viewing direction through volume data. It visualizes high-density structures, such as angio-graphic datasets so that it is frequently used in medical imaging systems. We have proposed an efficient two-step MIP acceleration method that uses the recent CPUs. First, we exploited SIMD instructions to reduce conditional branch instructions which take up a considerable part of whole rendering process, so that we improved rendering speed. Second, we proposed a new method, which accesses volume and image data successively by modifying the shear-warp rendering. This method improves memory access patterns so that cache misses are reduced. Using the current CPUs, our method improved the rendering speed by a factor of 7 than that of the shear-warp rendering.