Hybrid Data Visualization Based on Depth Complexity Histogram Analysis

In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi‐transparent geometry is present, correct rendering results require sorting of transparent structures. Additional comp...

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Published in:	Computer graphics forum Vol. 34; no. 1; pp. 74 - 85
Main Authors:	Lindholm, S., Falk, M., Sundén, E., Bock, A., Ynnerman, A., Ropinski, T.
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.02.2015
Subjects:	Algorithms Analysis Buffers Complexity Computer graphics Computer memory Data processing Data visualization Gain Histograms I.3.3 [Computer Graphics]: Picture/Image Generation Display-algorithms I.3.3 [Computer Graphics]: Picture/Image Generation Display—algorithms; I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—I.3.8 [Computer Graphics]: Applications I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-I.3.8 [Computer Graphics]: Applications Molecular biology Pixels ray tracing real-time rendering Rendering Scientific visualization Space weather Studies Utilization Visualization
ISSN:	0167-7055, 1467-8659, 1467-8659
Online Access:	Get full text
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Abstract	In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi‐transparent geometry is present, correct rendering results require sorting of transparent structures. Additional complexity is introduced as the contributions from volumetric data have to be partitioned according to the geometric objects in the scene. The A‐buffer, an enhanced framebuffer with additional per‐pixel information, has previously been introduced to deal with the complexity caused by transparent objects. In this paper, we present an optimized rendering algorithm for hybrid volume‐geometry data based on the A‐buffer concept. We propose two novel components for modern GPUs that tailor memory utilization to the depth complexity of individual pixels. The proposed components are compatible with modern A‐buffer implementations and yield performance gains of up to eight times compared to existing approaches through reduced allocation and reuse of fast cache memory. We demonstrate the applicability of our approach and its performance with several examples from molecular biology, space weather and medical visualization containing both, volumetric data and geometric structures. We present an A‐buffer based algorithm that achieves performance gains of up to eight times relative existing techniques. The algorithm contains two novel components which improve the utilization of the local cache memory on the GPU. This is particularly important for scenes with non‐uniform depth complexities and rapidly decreasing depth complexity histograms (DCHs).
AbstractList	In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi-transparent geometry is present, correct rendering results require sorting of transparent structures. Additional complexity is introduced as the contributions from volumetric data have to be partitioned according to the geometric objects in the scene. The A-buffer, an enhanced framebuffer with additional per-pixel information, has previously been introduced to deal with the complexity caused by transparent objects. In this paper, we present an optimized rendering algorithm for hybrid volume-geometry data based on the A-buffer concept. We propose two novel components for modern GPUs that tailor memory utilization to the depth complexity of individual pixels. The proposed components are compatible with modern A-buffer implementations and yield performance gains of up to eight times compared to existing approaches through reduced allocation and reuse of fast cache memory. We demonstrate the applicability of our approach and its performance with several examples from molecular biology, space weather, and medical visualization containing both, volumetric data and geometric structures. In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi-transparent geometry is present, correct rendering results require sorting of transparent structures. Additional complexity is introduced as the contributions from volumetric data have to be partitioned according to the geometric objects in the scene. The A-buffer, an enhanced framebuffer with additional per-pixel information, has previously been introduced to deal with the complexity caused by transparent objects. In this paper, we present an optimized rendering algorithm for hybrid volume-geometry data based on the A-buffer concept. We propose two novel components for modern GPUs that tailor memory utilization to the depth complexity of individual pixels. The proposed components are compatible with modern A-buffer implementations and yield performance gains of up to eight times compared to existing approaches through reduced allocation and reuse of fast cache memory. We demonstrate the applicability of our approach and its performance with several examples from molecular biology, space weather and medical visualization containing both, volumetric data and geometric structures. We present an A-buffer based algorithm that achieves performance gains of up to eight times relative existing techniques. The algorithm contains two novel components which improve the utilization of the local cache memory on the GPU. This is particularly important for scenes with non-uniform depth complexities and rapidly decreasing depth complexity histograms (DCHs). In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi‐transparent geometry is present, correct rendering results require sorting of transparent structures. Additional complexity is introduced as the contributions from volumetric data have to be partitioned according to the geometric objects in the scene. The A‐buffer, an enhanced framebuffer with additional per‐pixel information, has previously been introduced to deal with the complexity caused by transparent objects. In this paper, we present an optimized rendering algorithm for hybrid volume‐geometry data based on the A‐buffer concept. We propose two novel components for modern GPUs that tailor memory utilization to the depth complexity of individual pixels. The proposed components are compatible with modern A‐buffer implementations and yield performance gains of up to eight times compared to existing approaches through reduced allocation and reuse of fast cache memory. We demonstrate the applicability of our approach and its performance with several examples from molecular biology, space weather and medical visualization containing both, volumetric data and geometric structures. We present an A‐buffer based algorithm that achieves performance gains of up to eight times relative existing techniques. The algorithm contains two novel components which improve the utilization of the local cache memory on the GPU. This is particularly important for scenes with non‐uniform depth complexities and rapidly decreasing depth complexity histograms (DCHs).
Author	Lindholm, S. Sundén, E. Ropinski, T. Falk, M. Ynnerman, A. Bock, A.
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P., Bastos, R.: A survey of raster-based transparency techniques. Computers And Graphics 35, 6 (2011), 1023-1034. http://dx.doi.org/10.1016/j.cag.2011.07.006. – reference: [RBE08] Rössler, F., Botchen, R., Ertl, T.: Dynamic shader generation for GPU-based multi-volume ray casting. IEEE Computer Graphics and Applications 28, 5 (2008), 66-77. http://dx.doi.org/10.1109/MCG.2008.96. – reference: [EHK06] Engel, K., Hadwiger, M., Kniss, J. M., Rezk-Salama, C., Weiskopf, D.: Real-Time Volume Graphics. A. K. Peters, Ltd., Natick, MA, USA, 2006. – reference: [Mam89] Mammen, A.: Transparency and antialiasing algorithms implemented with the virtual pixel maps technique. IEEE Computer Graphics and Applications 9, 4 (1989), 43-55. http://dx.doi.org/10.1109/38.31463. – reference: [XOL04] Xie, H., Ofman, L., Lawrence, G.: Cone model for halo CMEs: Application to space weather forecasting. Journal of Geophysical Research: Space Physics 109, A3 (2004). http://dx.doi.org/10.1029/2003JA010226. – reference: [VF13] Vasilakis, A., Fudos, I.: Depth-fighting aware methods for multifragment rendering. IEEE Transactions on Visualization and Computer Graphics 19, 6 (2013), 967-977. http://dx.doi.org/10.1109/TVCG.2012.300. – reference: [GRT13] Günther, T., Rössl, C., Theisel, H.: Opacity optimization for 3D line fields. ACM Transactions on Graphics 32, 4 (July 2013), 120:1-120:8. http://dx.doi.org/10.1145/2461912.2461930. – reference: [YHGT10] Yang, J. C., Hensley, J., Grün, H., Thibieroz, N.: Real-time concurrent linked list construction on the GPU. Computer Graphics Forum 29, 4 (2010), 1297-1304. http://dx.doi.org/10.1111/j.1467-8659.2010.01725.x. – reference: [KGB09] Kainz, B., Grabner, M., Bornik, A., Hauswiesner, S., Muehl, J., Schmalstieg, D.: Ray-casting of multiple volumetric datasets with polyhedral boundaries on manycore GPUs. 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Snippet	In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and...
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SubjectTerms	Algorithms Analysis Buffers Complexity Computer graphics Computer memory Data processing Data visualization Gain Histograms I.3.3 [Computer Graphics]: Picture/Image Generation Display-algorithms I.3.3 [Computer Graphics]: Picture/Image Generation Display—algorithms; I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—I.3.8 [Computer Graphics]: Applications I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-I.3.8 [Computer Graphics]: Applications Molecular biology Pixels ray tracing real-time rendering Rendering Scientific visualization Space weather Studies Utilization Visualization
Title	Hybrid Data Visualization Based on Depth Complexity Histogram Analysis
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