2018
Ware, Colin; Turton, Terece; Bujack, Roxana; Samsel, Francesca; Shrivastava, Piyush; Rogers, David
Measuring and Modeling the Feature Detection Threshold Functions of Colormaps Journal Article
In: IEEE Transactions on Visualization and Computer Graphics, pp. 1-1, 2018, ISSN: 1077-2626, (LA-UR-18-21476).
Abstract | Links | BibTeX | Tags: color perception, Colormapping, feature extraction, frequency measurements, Image color analysis, sea measurements, sensitivity, spatial resolution, Task analysis
@article{8413174,
title = {Measuring and Modeling the Feature Detection Threshold Functions of Colormaps},
author = {Colin Ware and Terece Turton and Roxana Bujack and Francesca Samsel and Piyush Shrivastava and David Rogers},
url = {https://ieeexplore.ieee.org/document/8413174},
doi = {10.1109/TVCG.2018.2855742},
issn = {1077-2626},
year = {2018},
date = {2018-01-01},
journal = {IEEE Transactions on Visualization and Computer Graphics},
pages = {1-1},
abstract = {Pseudocoloring is one of the most common techniques used in scientific visualization. To apply pseudocoloring to a scalar field, the field value at each point is represented using one of a sequence of colors (called a colormap). One of the principles applied in generating colormaps is uniformity and previously the main method for determining uniformity has been the application of uniform color spaces. Here we present a new method for evaluating the feature discrimination threshold function across a colormap. The method is used in crowdsourced studies for the direct evaluation of nine colormaps for three feature sizes. The results are used to test the hypothesis that a uniform color space (CIELAB) gives too much weight to chromatic differences compared to luminance differences because of the way it was constructed. The hypothesis that feature discrimination can be predicted solely on the basis of luminance is also tested. The results reject both hypotheses and we demonstrate how reduced weights on the green-red and blue-yellow terms of the CIELAB color space creates a more accurate model when the task is the detection of smaller features in colormapped data. Both the method itself and modified CIELAB can be used in colormap design and evaluation.},
note = {LA-UR-18-21476},
keywords = {color perception, Colormapping, feature extraction, frequency measurements, Image color analysis, sea measurements, sensitivity, spatial resolution, Task analysis},
pubstate = {published},
tppubtype = {article}
}
Pseudocoloring is one of the most common techniques used in scientific visualization. To apply pseudocoloring to a scalar field, the field value at each point is represented using one of a sequence of colors (called a colormap). One of the principles applied in generating colormaps is uniformity and previously the main method for determining uniformity has been the application of uniform color spaces. Here we present a new method for evaluating the feature discrimination threshold function across a colormap. The method is used in crowdsourced studies for the direct evaluation of nine colormaps for three feature sizes. The results are used to test the hypothesis that a uniform color space (CIELAB) gives too much weight to chromatic differences compared to luminance differences because of the way it was constructed. The hypothesis that feature discrimination can be predicted solely on the basis of luminance is also tested. The results reject both hypotheses and we demonstrate how reduced weights on the green-red and blue-yellow terms of the CIELAB color space creates a more accurate model when the task is the detection of smaller features in colormapped data. Both the method itself and modified CIELAB can be used in colormap design and evaluation.
2017
Turton, Terece; Ware, Colin; Samsel, Francesca; Rogers, David
A Crowdsourced Approach to Colormap Assessment Proceedings Article
In: Lawonn, Kai; Smit, Noeska; Cunningham, Douglas (Ed.): EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3), The Eurographics Association, 2017, ISBN: 978-3-03868-041-3.
Abstract | Links | BibTeX | Tags: Colormapping, user interfaces
@inproceedings{Turton2017crowdsourced,
title = {A Crowdsourced Approach to Colormap Assessment},
author = {Terece Turton and Colin Ware and Francesca Samsel and David Rogers},
editor = {Kai Lawonn and Noeska Smit and Douglas Cunningham},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ACrowdsourcedApproachtoColormapAssessment.pdf},
doi = {10.2312/eurorv3.20171106},
isbn = {978-3-03868-041-3},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)},
publisher = {The Eurographics Association},
abstract = {Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.},
keywords = {Colormapping, user interfaces},
pubstate = {published},
tppubtype = {inproceedings}
}
Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.
: . .
1.
Ware, Colin; Turton, Terece; Bujack, Roxana; Samsel, Francesca; Shrivastava, Piyush; Rogers, David
Measuring and Modeling the Feature Detection Threshold Functions of Colormaps Journal Article
In: IEEE Transactions on Visualization and Computer Graphics, pp. 1-1, 2018, ISSN: 1077-2626, (LA-UR-18-21476).
@article{8413174,
title = {Measuring and Modeling the Feature Detection Threshold Functions of Colormaps},
author = {Colin Ware and Terece Turton and Roxana Bujack and Francesca Samsel and Piyush Shrivastava and David Rogers},
url = {https://ieeexplore.ieee.org/document/8413174},
doi = {10.1109/TVCG.2018.2855742},
issn = {1077-2626},
year = {2018},
date = {2018-01-01},
journal = {IEEE Transactions on Visualization and Computer Graphics},
pages = {1-1},
abstract = {Pseudocoloring is one of the most common techniques used in scientific visualization. To apply pseudocoloring to a scalar field, the field value at each point is represented using one of a sequence of colors (called a colormap). One of the principles applied in generating colormaps is uniformity and previously the main method for determining uniformity has been the application of uniform color spaces. Here we present a new method for evaluating the feature discrimination threshold function across a colormap. The method is used in crowdsourced studies for the direct evaluation of nine colormaps for three feature sizes. The results are used to test the hypothesis that a uniform color space (CIELAB) gives too much weight to chromatic differences compared to luminance differences because of the way it was constructed. The hypothesis that feature discrimination can be predicted solely on the basis of luminance is also tested. The results reject both hypotheses and we demonstrate how reduced weights on the green-red and blue-yellow terms of the CIELAB color space creates a more accurate model when the task is the detection of smaller features in colormapped data. Both the method itself and modified CIELAB can be used in colormap design and evaluation.},
note = {LA-UR-18-21476},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pseudocoloring is one of the most common techniques used in scientific visualization. To apply pseudocoloring to a scalar field, the field value at each point is represented using one of a sequence of colors (called a colormap). One of the principles applied in generating colormaps is uniformity and previously the main method for determining uniformity has been the application of uniform color spaces. Here we present a new method for evaluating the feature discrimination threshold function across a colormap. The method is used in crowdsourced studies for the direct evaluation of nine colormaps for three feature sizes. The results are used to test the hypothesis that a uniform color space (CIELAB) gives too much weight to chromatic differences compared to luminance differences because of the way it was constructed. The hypothesis that feature discrimination can be predicted solely on the basis of luminance is also tested. The results reject both hypotheses and we demonstrate how reduced weights on the green-red and blue-yellow terms of the CIELAB color space creates a more accurate model when the task is the detection of smaller features in colormapped data. Both the method itself and modified CIELAB can be used in colormap design and evaluation.
2.
Turton, Terece; Ware, Colin; Samsel, Francesca; Rogers, David
A Crowdsourced Approach to Colormap Assessment Proceedings Article
In: Lawonn, Kai; Smit, Noeska; Cunningham, Douglas (Ed.): EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3), The Eurographics Association, 2017, ISBN: 978-3-03868-041-3.
@inproceedings{Turton2017crowdsourced,
title = {A Crowdsourced Approach to Colormap Assessment},
author = {Terece Turton and Colin Ware and Francesca Samsel and David Rogers},
editor = {Kai Lawonn and Noeska Smit and Douglas Cunningham},
url = {http://datascience.dsscale.org/wp-content/uploads/2017/08/ACrowdsourcedApproachtoColormapAssessment.pdf},
doi = {10.2312/eurorv3.20171106},
isbn = {978-3-03868-041-3},
year = {2017},
date = {2017-01-01},
booktitle = {EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)},
publisher = {The Eurographics Association},
abstract = {Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Despite continual research and discussion on the perceptual effects of color in scientific visualization, psychophysical testing is often limited. In-person lab studies can be expensive and time-consuming while results can be difficult to extrapolate from meticulously controlled laboratory conditions to the real world of the visualization user. We draw on lessons learned from the use of crowdsourced participant pools in the behavioral sciences and information visualization to apply a crowdsourced approach to a classic psychophysical experiment assessing the ability of a colormap to impart metric information. We use an online presentation analogous to the color key task from Ware’s 1988 paper, Color Sequences for Univariate Maps, testing colormaps similar to those in the original paper along with contemporary colormap standards and new alternatives in the scientific visualization domain. We explore the issue of potential contamination from color deficient participants and establish that perceptual color research can appropriately leverage a crowdsourced participant pool without significant CVD concerns. The updated version of the Ware color key task also provides a method to assess and compare colormaps.