2017
Berres, Anne; Turton, Terece; Rogers, David; Ahrens, James; Petersen, Mark
Video Compression for Ocean Simulation Image Databases Proceedings Article
In: Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana (Ed.): Workshop on Visualization in Environmental Sciences (EnvirVis), The Eurographics Association, 2017, ISBN: 978-3-03868-040-6, (LA-UR-17-21590).
Abstract | Links | BibTeX | Tags: compression, visualization
@inproceedings{info:lanl-repo/lareport/LA-UR-17-21590,
title = {Video Compression for Ocean Simulation Image Databases},
author = {Anne Berres and Terece Turton and David Rogers and James Ahrens and Mark Petersen},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/VideoCompressionforOceanSimulationImageDatabases.pdf},
doi = {10.2312/envirvis.20171104},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-01-01},
booktitle = {Workshop on Visualization in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.},
howpublished = {Visualization in Environmental Sciences 2017 ; 2017-06-12 - 2017-06-13 ; Barcelona, Spain},
note = {LA-UR-17-21590},
keywords = {compression, visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.
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1.
Berres, Anne; Turton, Terece; Rogers, David; Ahrens, James; Petersen, Mark
Video Compression for Ocean Simulation Image Databases Proceedings Article
In: Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana (Ed.): Workshop on Visualization in Environmental Sciences (EnvirVis), The Eurographics Association, 2017, ISBN: 978-3-03868-040-6, (LA-UR-17-21590).
@inproceedings{info:lanl-repo/lareport/LA-UR-17-21590,
title = {Video Compression for Ocean Simulation Image Databases},
author = {Anne Berres and Terece Turton and David Rogers and James Ahrens and Mark Petersen},
editor = {Karsten Rink and Ariane Middel and Dirk Zeckzer and Roxana Bujack},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/VideoCompressionforOceanSimulationImageDatabases.pdf},
doi = {10.2312/envirvis.20171104},
isbn = {978-3-03868-040-6},
year = {2017},
date = {2017-01-01},
booktitle = {Workshop on Visualization in Environmental Sciences (EnvirVis)},
publisher = {The Eurographics Association},
abstract = {Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.},
howpublished = {Visualization in Environmental Sciences 2017 ; 2017-06-12 - 2017-06-13 ; Barcelona, Spain},
note = {LA-UR-17-21590},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Climate research requires monitoring a large range of spatial and temporal scales to understand the climate system and potential future impacts. Climate simulations are now run with very high resolution (1–10 km gridcells) ocean, sea ice, and atmosphere components, and can easily produce petabytes of output. This overloads storage systems and hinders visualization and analysis. Image databases can decrease storage sizes from petabytes of simulation output down to several hundred gigabytes of images.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.
In this paper, we introduce video compression as a method to further decrease database sizes by 2-4 orders of magnitude. We compare compression and access speeds, compressed sizes, and compression quality over a range of settings. Quality is assessed through image quality metrics and expert feedback. Overall, we were able to show that video compression techniques provide an efficient means of storing image databases at a shareable size, while preserving image quality. This enables the wise use of available disk space, so scientists can more easily study the physical features of interest.