Volume Upscaling Using Local Self-Examples for High Quality Volume Visualization
Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling, result in jagged artifacts around features and losses of high-frequency components. Based on the example-based up scaling framework, this pape...
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Published in | 2013 International Conference on Computer-Aided Design and Computer Graphics pp. 298 - 305 |
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Main Authors | , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.11.2013
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Subjects | |
Online Access | Get full text |
DOI | 10.1109/CADGraphics.2013.46 |
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Abstract | Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling, result in jagged artifacts around features and losses of high-frequency components. Based on the example-based up scaling framework, this paper presents a new high-quality volume up scaling technique, predicting the high-frequency components by searching for the best matched patch in the input volume. As each slice can be taken as an image, the existing image up scaling technique based on the local self-similarity assumption can be directly applied to achieve slice up scaling. We further validate that the local self-similarity assumption is still valid for 3D volumes, and we extend this technique to 3D volume up scaling, i.e., isotropic volume up scaling. We compare our volume up scaling technique with traditional linear and cubic spline interpolations, and demonstrate that our method can generate a higher quality volume with better shape and details preserved. The proposed volume up scaling technique is well suitable for legacy low-resolution volumes to improve their visual qualities in visualization and analysis. |
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AbstractList | Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling, result in jagged artifacts around features and losses of high-frequency components. Based on the example-based up scaling framework, this paper presents a new high-quality volume up scaling technique, predicting the high-frequency components by searching for the best matched patch in the input volume. As each slice can be taken as an image, the existing image up scaling technique based on the local self-similarity assumption can be directly applied to achieve slice up scaling. We further validate that the local self-similarity assumption is still valid for 3D volumes, and we extend this technique to 3D volume up scaling, i.e., isotropic volume up scaling. We compare our volume up scaling technique with traditional linear and cubic spline interpolations, and demonstrate that our method can generate a higher quality volume with better shape and details preserved. The proposed volume up scaling technique is well suitable for legacy low-resolution volumes to improve their visual qualities in visualization and analysis. |
Author | Qirui Wang Yubo Tao Clapworthy, Gordon Chao Wang Feng Dong Hai Lin |
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Snippet | Volume up scaling enlarges the size of a volume to make feature analysis more accurate and efficient. Linear interpolation, widely used in volume up scaling,... |
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SubjectTerms | Biomedical imaging Image reconstruction Image resolution Interpolation Rendering (computer graphics) self-examples slice upscaling Three-dimensional displays Visualization volume upscaling volume visualization |
Title | Volume Upscaling Using Local Self-Examples for High Quality Volume Visualization |
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