• Title/Summary/Keyword: 볼륨데이터

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A Sparse-ON Pixel Two-Dimensional 6/8 Modulation Code (저밀도 ON 픽셀 2차원 6/8 변조부호)

  • Hwang, Myungha;Lee, Jaejin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.10
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    • pp.833-837
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    • 2013
  • Since holographic data storages read and write information on a volume and the information is processed per page, it has the advantage of high recording density and data transfer rate. However, there are two major drawbacks like 2-dimensional intersymbol interference and interpage interference as the density between pixels increases. Furthermore, a bright page that contains many ON pixels influences the reliable detection of the neighboring pages, which causes the less number of pages stored in the storage volume. We propose a sparse-ON pixel two-dimensional modulation code with the code rate 6/8 for increasing the number of pages stored in the volume. The proposed code is compared to conventional 6/8 balanced code, and it shows similar or a little bit better performance than that of the balanced code. Therefore, the proposed code can increase the recording capacity without loss of the performance.

Extraction of Brain Boundary and Direct Volume Rendering of MRI Human Head Data (MR머리 영상의 뇌 경계선 추출 및 디렉트 볼륨 렌더링)

  • Song, Ju-Whan;Gwun, Ou-Bong;Lee, Kun
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.6
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    • pp.705-716
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    • 2002
  • This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

Effective method of accessing SHORE volumes (효과적인 SHORE 볼륨 접근 방법)

  • Ahn, Sung-Soo;Choi, Yun-Soo;Jin, Du-Seok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11c
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    • pp.1815-1818
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    • 2002
  • 사용자에게 서비스 할 데이터가 많을 경우 데이터베이스의 여러 볼륨에 저장해서 처리해야 할 경우가 발생한다. 볼륨이 여러 개일 경우 효과적이고 효율적인 접근 방법이 필요하다. 본 논문에서는 SHORE 저장 시스템을 이용할 경우에 효과적이고 효율적인 접근 방법을 알아보고자 한다. single thread, multi thread, multi process, socket 을 이용한 접근 방법을 살펴보고 multi thread 를 이용하는 방법이 가장 효율적인 것을 실험 결과를 통해서 보인다. SHORE thread 는 CPU bound 에 과련된 job 이 많은 경우는 process 를 사용했을 때에 비해 큰 효과가 없으나 I/0 bound 에 관련에 것일 경우는 multi process 를 사용한 것과 비슷한 효과가 있음을 알 수 있다.

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Optimized Volume Rendering Based on PyCUDA with Precomputed Density Query Acceleration (미리 계산된 밀도 쿼리 고속화를 이용한 PyCUDA 기반의 최적화된 볼륨 렌더링)

  • Sooho Lee;JongHyun Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.361-364
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    • 2023
  • 볼륨 렌더링은 3D 밀도 데이터를 가시화 할 때 활용되는 기술로써 이 알고리즘에서 중요한 것은 렌더링 시간 단축이며, 본 논문에서는 이 계산시간을 효율적으로 개선시킬 수 있는 방법을 제시한다. 렌더링의 처리시간은 탐색하는 횟수에 따라 결과 차이가 발생하지만, 탐색 횟수가 적을 경우 렌더링의 품질이 저하되고 반대인 경우에는 화질의 표현력은 높으나 많은 처리시간이 소요된다. 따라서 화질이 떨어지지 않는 최소의 탐색 방법이 요구되므로 본 논문에서는 밀도의 탐색 최적화와 시간별 밀도가 존재하는 위치를 예측하여 계산을 효율적으로 처리 할 수 있는 PyCUDA 프레임워크에 대해서 소개한다.

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Cell-Based Wavelet Compression Method for Volume Data (볼륨 데이터를 위한 셀 기반 웨이브릿 압축 기법)

  • Kim, Tae-Yeong;Sin, Yeong-Gil
    • Journal of KIISE:Computer Systems and Theory
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    • v.26 no.11
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    • pp.1285-1295
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    • 1999
  • 본 논문은 방대한 크기의 볼륨 데이타를 효율적으로 렌더링하기 위한 셀 기반 웨이브릿 압축 방법을 제시한다. 이 방법은 볼륨을 작은 크기의 셀로 나누고, 셀 단위로 웨이브릿 변환을 한 다음 복원 순서에 따른 런-길이(run-length) 인코딩을 수행하여 높은 압축율과 빠른 복원을 제공한다. 또한 최근 복원 정보를 캐쉬 자료 구조에 효율적으로 저장하여 복원 시간을 단축시키고, 에러 임계치의 정규화로 비정규화된 웨이브릿 압축보다 빠른 속도로 정규화된 압축과 같은 고화질의 이미지를 생성하였다. 본 연구의 성능을 평가하기 위하여 {{}} 해상도의 볼륨 데이타를 압축하여 쉬어-? 분해(shear-warp factorization) 알고리즘에 적용한 결과, 손상이 거의 없는 상태로 약 27:1의 압축율이 얻어졌고, 약 3초의 렌더링 시간이 걸렸다.Abstract This paper presents an efficient cell-based wavelet compression method of large volume data. Volume data is divided into individual cell of {{}} voxels, and then wavelet transform is applied to each cell. The transformed cell is run-length encoded according to the reconstruction order resulting in a fairly good compression ratio and fast reconstruction. A cache structure is used to speed up the process of reconstruction and a threshold normalization scheme is presented to produce a higher quality rendered image. We have combined our compression method with shear-warp factorization, which is an accelerated volume rendering algorithm. Experimental results show the space requirement to be about 27:1 and the rendering time to be about 3 seconds for {{}} data sets while preserving the quality of an image as like as using original data.

snap + XFS (네트워크 스토리지 상에서의 데이터 복구를 위한 스냅샷 개발)

  • Suk, Jin-Sun;Kim, Sun-Tae;No, Jae-Chun;Park, Sung-Sun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06b
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    • pp.294-297
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    • 2007
  • 다양한 스토리지와 파일 시스템들이 시스템의 신뢰도를 증가시키기 위해 스냅샷을 이용하고 있다. 하지만 현재 널리 사용되고 있는 볼륨 단에서의 스냅샷은 스냅샷 이미지를 생성하는데 필요한 시간이 볼륨의 크기에 비례하고 스냅샷 이미지를 생성하는 동안의 '파일시스템 입출력 성능'이 현저하게 저하되는 단점이 있다. 이러한 단점을 극복하기 위해 파일 시스템 단에서의 스냅샷 기법에 대한 연구가 진행되어 왔으며 "snapFS", "Ext3Cow" 그리고 "New version of SnapFS" 등의 파일 시스템들이 개발 되었다. 본 논문에서는 네트워크로 연결된 스토리지 상에서의 데이터 복구를 효율적으로 처리하기 위해 대용량 파일을 처리하는데 적합한 XFS에 스냅샷 기능을 추가한 snap+XFS에 대해 언급한다.

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Real-Time Stereoscopic Visualization of Very Large Volume Data on CAVE (CAVE상에서의 방대한 볼륨 데이타의 실시간 입체 영상 가시화)

  • 임무진;이중연;조민수;이상산;임인성
    • 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.

Adaptive Weight Adjusted Catmull-Rom Spline Interpolation Based on Pixel Intensity Variation for Medical Imaging Volume Visualization (의료영상 볼륨가시화를 위한 화소 값의 변화도에 따른 적응적 가중치를 적용한 캐트멀-롬 스플라인 보간법)

  • Lee, Hae-Na;Yoo, Sun K.
    • Journal of Korea Multimedia Society
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    • v.16 no.2
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    • pp.147-159
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    • 2013
  • In medical visualization, volume visualization is widely used. Applying 3D images to diagnose requires high resolution and accurately implement visualization techniques are being researched accordingly. However, when a three-dimensional image volume visualization is implemented using volume data, aliasing will occur since using discrete data. Supersampling method, getting lots of samples, is used to reduce artifacts. One of the supersampling methods is Catmull-rom spline. This method calculates accurate interpolation value because it is easy to compute and pass through control points. But, Catmull-rom spline method occurs overshoot or undershoot in large gradient of pixel values. So, interpolated values are different from original signal. In this paper, we propose an adaptive adjusting weights interpolation method using Gaussian function. Proposed method shows that overshoot is reduced on the point has a large gradient and PSNR is higher than other interpolated image results.

Method of Fast Interpolation of B-Spline Volumes for Reconstructing the Heterogeneous Model of Bones from CT Images (CT 영상에서 뼈의 불균질 모델 생성을 위한 B-스플라인 볼륨의 빠른 보간 방법)

  • Park, Jun Hong;Kim, Byung Chul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.40 no.4
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    • pp.373-379
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    • 2016
  • It is known that it is expedient to represent the distribution of the properties of a bone with complex heterogeneity as B-spline volume functions. For B-spline-based representation, the pixel values of CT images are interpolated by B-spline volume functions. However, the CT images of a bone are three-dimensional and very large, and hence a large amount of memory and long computation time for the interpolation are required. In this study, a method for resolving these problems is proposed. In the proposed method, the B-spline volume interpolation problem is simplified by using the uniformity of pixel spacing of the image and the properties of B-spline basis functions. This results in a reduction in computation time and the amount of memory used. The proposed method was implemented and it was verified that the computation time and the amount of memory used were reduced.

A Slice Information Based Labeling Algorithm for 3-D Volume Data (Slice 정보에 기반한 3차원 볼륨 데이터의 레이블링 알고리즘)

  • 최익환;최현주;이병일;최흥국
    • Journal of KIISE:Software and Applications
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    • v.31 no.7
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    • pp.922-928
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    • 2004
  • We propose a new 3 dimensional labeling method based on slice information for the volume data. This method is named SIL (Slice Information based Labeling). Compare to the conventional algorithms, it has advantages that the use of memory is efficient and it Is possible to combine with a variety of 2 dimensional labeling algorithms for finding an appropriate labeling algorithm to its application. In this study, we applied SIL to confocal microscopy images of cervix cancer cell and compared the results of labeling. According to the measurement, we found that the speed of Sd combined with, CCCL (Contour based Connected Component Labeling) is almost 2 times higher than that of other methods. In conclusion, considering that the performance of labeling depends on a kind of image, we obtained that the proposed method provide better result for the confocal microscopy cell volume data.