Methods for Compensating Contrast Effects in Information Visualization
Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first leve...
Saved in:
| Published in | Computer graphics forum Vol. 33; no. 3; pp. 231 - 240 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Blackwell Publishing Ltd
01.06.2014
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel‐based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains. |
|---|---|
| AbstractList | Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel‐based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains. Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations between features and groups appear as visual patterns in the visualization. However, optical illusions may bias the perception at the first level of the analysis process. For instance, in pixel-based visualizations contrast effects make pixels appear brighter if surrounded by a darker area, which distorts the encoded metric quantity of the data points. Even if we are aware of these perceptual issues, our visual cognition system is not able to compensate these effects accurately. To overcome this limitation, we present a color optimization algorithm based on perceptual metrics and color perception models to reduce physiological contrast or color effects. We evaluate our technique with a user study and find that the technique doubles the accuracy of users comparing and estimating color encoded data values. Since the presented technique can be used in any application without adaption to the visualization itself, we are able to demonstrate its effectiveness on data visualizations in different domains. [PUBLICATION ABSTRACT] |
| Author | Keim, D. A. Mittelstädt, S. Stoffel, A. |
| Author_xml | – sequence: 1 givenname: S. surname: Mittelstädt fullname: Mittelstädt, S. organization: University of Konstanz, Germany – sequence: 2 givenname: A. surname: Stoffel fullname: Stoffel, A. organization: University of Konstanz, Germany – sequence: 3 givenname: D. A. surname: Keim fullname: Keim, D. A. organization: University of Konstanz, Germany |
| BookMark | eNp9kE1vGyEQhlGUSHXcHvoPVsolOawDCyxwjKzYseS2UdUPKReE2VmHZA0OrJWPXx9qtzlYSrnAiOcdzTzH6NAHDwh9JnhE8jm3y3ZEKirUARoQVotS1lwdogEm-S0w5x_QcUp3GGMmaj5Aky_Q34YmFW2IxTis1uCT6Z1f5sL30aS-uGxbsH0qnC9mPmOr_B988culjency7b6iI5a0yX49Pceop-Tyx_jq3L-bTobX8xLS2upSs4koZJZAMmBLhiriJXYWiyobNoF4aCgUbVZSNFIqbipKl7bqm4qYE2DFR2i013fdQwPG0i9XrlkoeuMh7BJmnCuBFac8Iye7KF3YRN9ni5TjGchjFaZOttRNoaUIrR6Hd3KxGdNsP5jVGejems0s-d7rHX9dv0synX_Szy6Dp7fb63H08m_RLlLuNTD01vCxHtdCyq4_v11qq_JzffrGzLVc_oKFjmXpA |
| CitedBy_id | crossref_primary_10_1109_TVCG_2019_2903945 crossref_primary_10_1007_s00371_019_01706_6 crossref_primary_10_1016_j_cag_2024_103906 crossref_primary_10_1109_TVCG_2017_2743978 crossref_primary_10_1109_TVCG_2021_3085327 crossref_primary_10_1016_j_cola_2019_100911 crossref_primary_10_1109_TVCG_2017_2744359 crossref_primary_10_3389_fpsyg_2023_1097834 crossref_primary_10_1111_cgf_12739 crossref_primary_10_1016_j_cag_2021_08_003 crossref_primary_10_1109_TVCG_2016_2598618 crossref_primary_10_1109_TVCG_2020_3030395 crossref_primary_10_1109_TVCG_2023_3346640 crossref_primary_10_1111_cgf_14313 crossref_primary_10_1111_cgf_12633 crossref_primary_10_1111_cgf_13611 crossref_primary_10_1109_TVCG_2020_3029413 crossref_primary_10_1109_TVCG_2020_3028955 crossref_primary_10_1109_TVCG_2021_3070876 crossref_primary_10_1109_TVCG_2015_2489649 crossref_primary_10_3389_fpsyg_2022_828545 |
| Cites_doi | 10.1038/nature03271 10.1179/000870403235002042 10.1109/38.135886 10.1163/156856887X00222 10.1109/2945.841121 10.1016/S0734-189X(85)80004-9 10.1109/VISUAL.1995.480803 10.1145/2470654.2481283 10.1002/(SICI)1520-6378(199606)21:3<221::AID-COL4>3.0.CO;2-U 10.1016/S0042-6989(99)00119-4 10.1111/0033-0124.00077 10.1093/acprof:oso/9780195187168.001.0001 10.1117/1.1635368 10.7717/peerj.146 10.1002/9781119975595 10.1109/MCG.1986.276688 10.1109/38.7760 10.1080/00031305.1983.10482720 10.1063/1.4822401 10.1037/0033-295X.106.4.795 10.1109/TVCG.2012.315 10.1109/TVCG.2008.112 10.1016/j.visres.2004.09.027 10.1002/9781118653128 |
| ContentType | Journal Article |
| Copyright | 2014 The Author(s) Computer Graphics Forum © 2014 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. 2014 The Eurographics Association and John Wiley & Sons Ltd. |
| Copyright_xml | – notice: 2014 The Author(s) Computer Graphics Forum © 2014 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. – notice: 2014 The Eurographics Association and John Wiley & Sons Ltd. |
| DBID | BSCLL AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D F28 FR3 |
| DOI | 10.1111/cgf.12379 |
| DatabaseName | Istex CrossRef Computer and Information Systems Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ANTE: Abstracts in New Technology & Engineering Engineering Research Database |
| DatabaseTitle | CrossRef Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional Engineering Research Database ANTE: Abstracts in New Technology & Engineering |
| DatabaseTitleList | CrossRef Computer and Information Systems Abstracts Technology Research Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1467-8659 |
| EndPage | 240 |
| ExternalDocumentID | 3372545471 10_1111_cgf_12379 CGF12379 ark_67375_WNG_P1ZRPZ1G_L |
| Genre | article Feature |
| GroupedDBID | .3N .4S .DC .GA .Y3 05W 0R~ 10A 15B 1OB 1OC 29F 31~ 33P 3SF 4.4 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 5GY 5HH 5LA 5VS 66C 6J9 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 8VB 930 A03 AAESR AAEVG AAHHS AANLZ AAONW AASGY AAXRX AAZKR ABCQN ABCUV ABDBF ABDPE ABEML ABPVW ACAHQ ACBWZ ACCFJ ACCZN ACFBH ACGFS ACPOU ACSCC ACXBN ACXQS ADBBV ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN ADZOD AEEZP AEGXH AEIGN AEIMD AEMOZ AENEX AEQDE AEUQT AEUYR AFBPY AFEBI AFFNX AFFPM AFGKR AFPWT AFZJQ AHBTC AHEFC AITYG AIURR AIWBW AJBDE AJXKR AKVCP ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN AMBMR AMYDB ARCSS ASPBG ATUGU AUFTA AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BSCLL BY8 CAG COF CS3 CWDTD D-E D-F DCZOG DPXWK DR2 DRFUL DRSTM DU5 EAD EAP EBA EBO EBR EBS EBU EDO EJD EMK EST ESX F00 F01 F04 F5P FEDTE FZ0 G-S G.N GODZA H.T H.X HF~ HGLYW HVGLF HZI HZ~ I-F IHE IX1 J0M K1G K48 LATKE LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LW6 LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ O66 O9- OIG P2W P2X P4D PALCI PQQKQ Q.N Q11 QB0 QWB R.K RDJ RIWAO RJQFR ROL RX1 SAMSI SUPJJ TH9 TN5 TUS UB1 V8K W8V W99 WBKPD WIH WIK WOHZO WQJ WRC WXSBR WYISQ WZISG XG1 ZL0 ZZTAW ~IA ~IF ~WT AAHQN AAMNL AANHP AAYCA ACRPL ACUHS ACYXJ ADNMO AFWVQ AHQJS ALVPJ AAYXX ADMLS AEYWJ AGHNM AGQPQ AGYGG CITATION 7SC 8FD AAMMB AEFGJ AGXDD AIDQK AIDYY JQ2 L7M L~C L~D F28 FR3 |
| ID | FETCH-LOGICAL-c3689-5481384cee85e3b4421c80cc0738dfb15e9ed96ab87d8895a2256c26d2e4dd093 |
| IEDL.DBID | DR2 |
| ISSN | 0167-7055 |
| IngestDate | Fri Jul 11 16:07:01 EDT 2025 Fri Jul 25 23:42:47 EDT 2025 Tue Jul 01 02:23:04 EDT 2025 Thu Apr 24 23:13:08 EDT 2025 Wed Jan 22 16:24:44 EST 2025 Wed Oct 30 09:52:56 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3689-5481384cee85e3b4421c80cc0738dfb15e9ed96ab87d8895a2256c26d2e4dd093 |
| Notes | istex:6F7EE1C415B50CB8C42F4C2A74AA69FCC047DBAF ArticleID:CGF12379 Supporting Information ark:/67375/WNG-P1ZRPZ1G-L SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| PQID | 1545016432 |
| PQPubID | 30877 |
| PageCount | 10 |
| ParticipantIDs | proquest_miscellaneous_1559709515 proquest_journals_1545016432 crossref_primary_10_1111_cgf_12379 crossref_citationtrail_10_1111_cgf_12379 wiley_primary_10_1111_cgf_12379_CGF12379 istex_primary_ark_67375_WNG_P1ZRPZ1G_L |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | June 2014 |
| PublicationDateYYYYMMDD | 2014-06-01 |
| PublicationDate_xml | – month: 06 year: 2014 text: June 2014 |
| PublicationDecade | 2010 |
| PublicationPlace | Oxford |
| PublicationPlace_xml | – name: Oxford |
| PublicationTitle | Computer graphics forum |
| PublicationTitleAlternate | Computer Graphics Forum |
| PublicationYear | 2014 |
| Publisher | Blackwell Publishing Ltd |
| Publisher_xml | – name: Blackwell Publishing Ltd |
| References | Anderson B.L., Winawer J.: Image segmentation and lightness perception. Nature 434, 7029 (2005), 79-83. 3 Blakeslee B., Pasieka W., McCourt M.E.: Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including white, howe and simultaneous brightness contrast. Vision Research 45, 5 (2005), 607-615. 3 Brewer C.A.: Prediction of simultaneous contrast between map colors with hunt's model of color appearance. Color Research and Application 21, 3 (1996), 221-235. 2 Andrienko N., Andrienko G.: Exploratory Analysis of Spatial and Temporal Data. Springer, 2006. 3 Harrower M., Brewer C.: Colorbrewer.org: An online tool for selecting colour schemes for maps. The Cartographic Journal 40, 1 (2003), 27-37. 2 Brewer C.A.: Evaluation of a model for predicting simultaneous contrast on color maps. The Professional Geographer 49, 3 (1997), 280-294. 2 Levkowitz H., Herman G.T.: The design and evaluation of color scales for image data. IEEE Computer Graphics and Applications 12, 1 (1992), 72-80. 2 Kuhn G.R., Oliveira M.M., Fernandes L.A.: An efficient naturalness-preserving image-recoloring method for dichromats. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1747-1754. 2 Cleveland W.S., McGill R.: A color-caused optical illusion on a statistical graph. The American Statistician 37, 2 (1983), 101-105. 2 Fairchild M.D., Johnson G.M.: iCAM framework for image appearance, differences, and quality. Journal of Electronic Imaging 13, 1 (2004), 126-138. 3, 4 Robertson P.K., O'Callaghan J.F.: The generation of color sequences for univariate and bivariate mapping. IEEE Computer Graphics and Applications 6, 2 (1986), 24-32. 2 Treisman A.: Preattentive processing in vision. Computer Vision, Graphics, and Image Processing 31, 2 (1985), 156-177. 1 Gilchrist A., Kossyfidis C., Bonato F., Agostini T., Cataliotti J., Li X., Spehar B., Annan V., Economou E.: An anchoring theory of lightness perception. Psychological Review 106, 4 (1999), 795-809. 3 Shi V., Cui J., Troncoso X.G., Macknik S.L., Martinez-Conde S.: Effect of stimulus width on simultaneous contrast. PeerJ 1 (2013), 146. 4 Hunt R. W. G., Pointer M.R.: Measuring Colour. John Wiley & Sons, 2011. 2 Keim D.: Designing pixel-oriented visualization techniques: Theory and applications. IEEE Transactions on Visualization and Computer Graphics 6, 1 (2000), 59-78. 2, 6 Gilchrist A.: Seeing Black and White. Oxford University Press, 2006. 3 Rogowitz B., Treinish L., Bryson S.: How not to lie with visualization. Computers in Physics 10, 3 (1996), 268-273. 2 Blakeslee B., McCourt M.E.: A multiscale spatial filtering account of the white effect, simultaneous brightness contrast and grating induction. Vision Research 39, 26 (1999), 4361-4377. 4 Young R.A.: The Gaussian derivative model for spatial vision: I. retinal mechanisms. Spatial Vision 2, 4 (1987), 273-293. 4 Fairchild M.D.: Color Appearance Models. John Wiley & Sons, 2013. 2 Ware C.: Color sequences for univariate maps: Theory, experiments and principles. IEEE Computer Graphics and Applications 8, 5 (1988), 41-49. 1, 2, 6, 7, 8 1987; 2 2013; 1 2000; 6 2012 2011 2005; 434 2008; 14 2009 2008 1996 2006 1997; 49 1995 2005 2002 1999; 106 1983; 37 1992; 12 1996; 10 2005; 45 2002; 2002 1999; 39 1988; 8 2004; 13 1986; 6 2013 2003; 40 1985; 31 1996; 21 e_1_2_8_27_2 e_1_2_8_29_2 e_1_2_8_23_2 Andrienko N. (e_1_2_8_2_2) 2006 e_1_2_8_25_2 e_1_2_8_26_2 Cleveland W.S. (e_1_2_8_9_2) 1983; 37 e_1_2_8_4_2 e_1_2_8_3_2 e_1_2_8_6_2 e_1_2_8_5_2 e_1_2_8_7_2 Moroney N. (e_1_2_8_24_2) 2002 e_1_2_8_20_2 e_1_2_8_22_2 e_1_2_8_16_2 e_1_2_8_18_2 e_1_2_8_19_2 e_1_2_8_12_2 e_1_2_8_13_2 Bergman L.D. (e_1_2_8_8_2) 1995 e_1_2_8_14_2 e_1_2_8_15_2 Kindlmann G. (e_1_2_8_21_2) 2002 Healey C. (e_1_2_8_17_2) 1996 e_1_2_8_31_2 e_1_2_8_30_2 e_1_2_8_10_2 e_1_2_8_33_2 e_1_2_8_11_2 e_1_2_8_32_2 Tominski C. (e_1_2_8_28_2) 2008 |
| References_xml | – reference: Fairchild M.D.: Color Appearance Models. John Wiley & Sons, 2013. 2 – reference: Treisman A.: Preattentive processing in vision. Computer Vision, Graphics, and Image Processing 31, 2 (1985), 156-177. 1 – reference: Keim D.: Designing pixel-oriented visualization techniques: Theory and applications. IEEE Transactions on Visualization and Computer Graphics 6, 1 (2000), 59-78. 2, 6 – reference: Fairchild M.D., Johnson G.M.: iCAM framework for image appearance, differences, and quality. Journal of Electronic Imaging 13, 1 (2004), 126-138. 3, 4 – reference: Anderson B.L., Winawer J.: Image segmentation and lightness perception. Nature 434, 7029 (2005), 79-83. 3 – reference: Brewer C.A.: Evaluation of a model for predicting simultaneous contrast on color maps. The Professional Geographer 49, 3 (1997), 280-294. 2 – reference: Levkowitz H., Herman G.T.: The design and evaluation of color scales for image data. IEEE Computer Graphics and Applications 12, 1 (1992), 72-80. 2 – reference: Andrienko N., Andrienko G.: Exploratory Analysis of Spatial and Temporal Data. Springer, 2006. 3 – reference: Blakeslee B., McCourt M.E.: A multiscale spatial filtering account of the white effect, simultaneous brightness contrast and grating induction. Vision Research 39, 26 (1999), 4361-4377. 4 – reference: Harrower M., Brewer C.: Colorbrewer.org: An online tool for selecting colour schemes for maps. The Cartographic Journal 40, 1 (2003), 27-37. 2 – reference: Robertson P.K., O'Callaghan J.F.: The generation of color sequences for univariate and bivariate mapping. IEEE Computer Graphics and Applications 6, 2 (1986), 24-32. 2 – reference: Blakeslee B., Pasieka W., McCourt M.E.: Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including white, howe and simultaneous brightness contrast. Vision Research 45, 5 (2005), 607-615. 3 – reference: Shi V., Cui J., Troncoso X.G., Macknik S.L., Martinez-Conde S.: Effect of stimulus width on simultaneous contrast. PeerJ 1 (2013), 146. 4 – reference: Brewer C.A.: Prediction of simultaneous contrast between map colors with hunt's model of color appearance. Color Research and Application 21, 3 (1996), 221-235. 2 – reference: Gilchrist A.: Seeing Black and White. Oxford University Press, 2006. 3 – reference: Gilchrist A., Kossyfidis C., Bonato F., Agostini T., Cataliotti J., Li X., Spehar B., Annan V., Economou E.: An anchoring theory of lightness perception. Psychological Review 106, 4 (1999), 795-809. 3 – reference: Hunt R. W. G., Pointer M.R.: Measuring Colour. John Wiley & Sons, 2011. 2 – reference: Ware C.: Color sequences for univariate maps: Theory, experiments and principles. IEEE Computer Graphics and Applications 8, 5 (1988), 41-49. 1, 2, 6, 7, 8 – reference: Rogowitz B., Treinish L., Bryson S.: How not to lie with visualization. Computers in Physics 10, 3 (1996), 268-273. 2 – reference: Young R.A.: The Gaussian derivative model for spatial vision: I. retinal mechanisms. Spatial Vision 2, 4 (1987), 273-293. 4 – reference: Cleveland W.S., McGill R.: A color-caused optical illusion on a statistical graph. The American Statistician 37, 2 (1983), 101-105. 2 – reference: Kuhn G.R., Oliveira M.M., Fernandes L.A.: An efficient naturalness-preserving image-recoloring method for dichromats. IEEE Transactions on Visualization and Computer Graphics 14, 6 (2008), 1747-1754. 2 – year: 2011 – volume: 37 start-page: 101 issue: 2 year: 1983 end-page: 105 article-title: A color‐caused optical illusion on a statistical graph publication-title: The American Statistician – volume: 10 start-page: 268 issue: 3 year: 1996 end-page: 273 article-title: How not to lie with visualization publication-title: Computers in Physics – year: 2009 – volume: 106 start-page: 795 issue: 4 year: 1999 end-page: 809 article-title: An anchoring theory of lightness perception publication-title: Psychological Review – volume: 434 start-page: 79 issue: 7029 year: 2005 end-page: 83 article-title: Image segmentation and lightness perception publication-title: Nature – volume: 40 start-page: 27 issue: 1 year: 2003 end-page: 37 article-title: An online tool for selecting colour schemes for maps publication-title: The Cartographic Journal – year: 2005 – start-page: 1746 year: 2012 end-page: 1757 – volume: 39 start-page: 4361 issue: 26 year: 1999 end-page: 4377 article-title: A multiscale spatial filtering account of the white effect, simultaneous brightness contrast and grating induction publication-title: Vision Research – start-page: 263 year: 1996 end-page: 270 – volume: 21 start-page: 221 issue: 3 year: 1996 end-page: 235 article-title: Prediction of simultaneous contrast between map colors with hunt's model of color appearance publication-title: Color Research and Application – volume: 31 start-page: 156 issue: 2 year: 1985 end-page: 177 article-title: Preattentive processing in vision publication-title: Computer Vision, Graphics, and Image Processing – start-page: 373 year: 2008 end-page: 380 – volume: 8 start-page: 41 issue: 5 year: 1988 end-page: 49 article-title: Color sequences for univariate maps: Theory, experiments and principles publication-title: IEEE Computer Graphics and Applications – start-page: 299 year: 2002 end-page: 306 – volume: 12 start-page: 72 issue: 1 year: 1992 end-page: 80 article-title: The design and evaluation of color scales for image data publication-title: IEEE Computer Graphics and Applications – start-page: 118 year: 1995 end-page: 125 – volume: 13 start-page: 126 issue: 1 year: 2004 end-page: 138 article-title: iCAM framework for image appearance, differences, and quality publication-title: Journal of Electronic Imaging – volume: 6 start-page: 59 issue: 1 year: 2000 end-page: 78 article-title: Designing pixel‐oriented visualization techniques: Theory and applications publication-title: IEEE Transactions on Visualization and Computer Graphics – year: 2006 – volume: 14 start-page: 1747 issue: 6 year: 2008 end-page: 1754 article-title: An efficient naturalness‐preserving image‐recoloring method for dichromats publication-title: IEEE Transactions on Visualization and Computer Graphics – volume: 1 start-page: 146 year: 2013 article-title: Effect of stimulus width on simultaneous contrast publication-title: PeerJ – volume: 2 start-page: 273 issue: 4 year: 1987 end-page: 293 article-title: The Gaussian derivative model for spatial vision: I. retinal mechanisms publication-title: Spatial Vision – volume: 6 start-page: 24 issue: 2 year: 1986 end-page: 32 article-title: The generation of color sequences for univariate and bivariate mapping publication-title: IEEE Computer Graphics and Applications – volume: 49 start-page: 280 issue: 3 year: 1997 end-page: 294 article-title: Evaluation of a model for predicting simultaneous contrast on color maps publication-title: The Professional Geographer – volume: 2002 start-page: 23 year: 2002 end-page: 27 – start-page: 2069 year: 2013 end-page: 2078 – volume: 45 start-page: 607 issue: 5 year: 2005 end-page: 615 article-title: Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including white, howe and simultaneous brightness contrast publication-title: Vision Research – year: 2013 – ident: e_1_2_8_3_2 doi: 10.1038/nature03271 – ident: e_1_2_8_16_2 doi: 10.1179/000870403235002042 – ident: e_1_2_8_22_2 doi: 10.1109/38.135886 – ident: e_1_2_8_32_2 – ident: e_1_2_8_33_2 doi: 10.1163/156856887X00222 – ident: e_1_2_8_30_2 – ident: e_1_2_8_19_2 doi: 10.1109/2945.841121 – ident: e_1_2_8_29_2 doi: 10.1016/S0734-189X(85)80004-9 – start-page: 118 volume-title: Proceedings of the IEEE Conference on Visualization year: 1995 ident: e_1_2_8_8_2 doi: 10.1109/VISUAL.1995.480803 – ident: e_1_2_8_13_2 doi: 10.1145/2470654.2481283 – ident: e_1_2_8_6_2 doi: 10.1002/(SICI)1520-6378(199606)21:3<221::AID-COL4>3.0.CO;2-U – ident: e_1_2_8_12_2 – ident: e_1_2_8_4_2 doi: 10.1016/S0042-6989(99)00119-4 – ident: e_1_2_8_7_2 doi: 10.1111/0033-0124.00077 – ident: e_1_2_8_14_2 doi: 10.1093/acprof:oso/9780195187168.001.0001 – start-page: 373 volume-title: Proceedings of the 12th International Conference on Information Visualisation year: 2008 ident: e_1_2_8_28_2 – ident: e_1_2_8_11_2 doi: 10.1117/1.1635368 – ident: e_1_2_8_27_2 doi: 10.7717/peerj.146 – ident: e_1_2_8_18_2 doi: 10.1002/9781119975595 – ident: e_1_2_8_25_2 doi: 10.1109/MCG.1986.276688 – ident: e_1_2_8_31_2 doi: 10.1109/38.7760 – start-page: 263 volume-title: Proceedings of Visualization. year: 1996 ident: e_1_2_8_17_2 – volume: 37 start-page: 101 issue: 2 year: 1983 ident: e_1_2_8_9_2 article-title: A color‐caused optical illusion on a statistical graph publication-title: The American Statistician doi: 10.1080/00031305.1983.10482720 – ident: e_1_2_8_26_2 doi: 10.1063/1.4822401 – ident: e_1_2_8_15_2 doi: 10.1037/0033-295X.106.4.795 – volume-title: Exploratory Analysis of Spatial and Temporal Data year: 2006 ident: e_1_2_8_2_2 – start-page: 23 volume-title: Proceedings of the Color and Imaging Conference year: 2002 ident: e_1_2_8_24_2 – ident: e_1_2_8_23_2 doi: 10.1109/TVCG.2012.315 – start-page: 299 volume-title: Proceedings of the conference on Visualization year: 2002 ident: e_1_2_8_21_2 – ident: e_1_2_8_20_2 doi: 10.1109/TVCG.2008.112 – ident: e_1_2_8_5_2 doi: 10.1016/j.visres.2004.09.027 – ident: e_1_2_8_10_2 doi: 10.1002/9781118653128 |
| SSID | ssj0004765 |
| Score | 2.2492182 |
| Snippet | Color, as one of the most effective visual variables, is used in many techniques to encode and group data points according to different features. Relations... |
| SourceID | proquest crossref wiley istex |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 231 |
| SubjectTerms | Algorithms Analysis Categories and Subject Descriptors (according to ACM CCS) Color Data points Data visualization Distortion I.3.3 [Computer Graphics]: Picture/Image Generation-Display algorithms Information processing Optical illusion Perception Perceptions Physiology Visual Visualization |
| Title | Methods for Compensating Contrast Effects in Information Visualization |
| URI | https://api.istex.fr/ark:/67375/WNG-P1ZRPZ1G-L/fulltext.pdf https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fcgf.12379 https://www.proquest.com/docview/1545016432 https://www.proquest.com/docview/1559709515 |
| Volume | 33 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ3fS9xAEMcH0Rf7UH-0pWdV1lJKX3K42R_Z4JOIdyIqIrUVKSz7K0UssVzuoPSvdye_PKVC8S1wc7DZycx-N5n5LMCn1EqDnLpEBm4SbmmRIOU7QXQXp3kmQsAX-qdn8uiSH1-JqwXY63phGj5E_8INI6PO1xjgxlZzQe5-FsOYdjNs3sNaLRREFw_oKJ5J0XG9kRjTUoWwiqf_56O1aAmn9c8joTkvV-v1ZrQCP7qRNmUmt8PZ1A7d3ycQxxfeyiq8bnUo2W8enDVYCOU6vJqjE76B0Wl9unRFoq4lmDfijtdglTRBpNXEVFPSsI8rclOStq8J_Uy-3VTYq9l0eL6Fy9Hh14OjpD12IXFMqjyJexjKFI-rpxKBWc5T6tSuczEZKF9YKkIefC6NVZlXKhcmpgTpUunTwL3fzdk7WCzvyvAeSOGcsMzb3LCMc-cUpQWzUuaeOU-pH8CXzgHatUxyPBrjl-72JnFqdD01A_jYm_5uQBz_Mvpce7G3MJNbrFzLhP5-Ntbn9Pri_JqO9ckANjs36zZoK41qEoljLB3ATv9zDDf8hmLKcDdDm7gDQ1kq4thrnz4_Gn0wHtUXG_9v-gGWoyTjTTHaJixOJ7OwFWXP1G7Xz_c9t738dw |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ3daxQxEMCH2j6oD36Lp1WjiPiyR7ObZBPwRap3p94dpbRaCiXka6W0bMvtHYh_vZn98ioK4tvCzkI2szOZZGd-A_AqtcIgpy4RgZmEWVokSPlOEN3FqMp5CHigP5uLySH7dMSPNuBtVwvT8CH6Aze0jNpfo4HjgfSalbtvxTD63Vxdgy3s6I3k_Pf7v-BRLBe8I3sjM6blCmEeT__oldVoCyf2-5VQcz1grVec0W046cbaJJqcDVdLO3Q_fsM4_u_L3IFbbShK3jXfzl3YCOU9uLkGKLwPo1ndYLoiMbQl6DriptdgojRBqtXCVEvS4I8rclqStrQJVU2-nFZYrtkUeT6Aw9GHg91J0nZeSFwmpEriNoZmksUFVPKQWcZS6uSOc9EfSF9YyoMKXgljZe6lVNxEryBcKnwamPc7KnsIm-VFGR4BKZzjNvNWmSxnzDlJaZFZIZTPnKfUD-BNpwHtWiw5dsc41932JE6NrqdmAC970cuGxfEnode1GnsJszjD5LWc66_zsd6jx_t7x3SspwPY7vSsW7utNAaUCB3L0gG86G9Hi8PfKKYMFyuUiZswjEx5HHut1L-PRu-OR_XF438XfQ7XJwezqZ5-nH9-AjdihMaa3LRt2FwuVuFpjIKW9ln9sf8Ee_UAog |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3raxQxEB9qC6IffIunVaOI-GWPy-axCX6S1r2q7XEUq6UIYfNYKZVtub0D8a83sy-voiB-W9hZyGYyk98kM78BeJFaWSBPXSIDLxJuaZkgy3eC1F2c6kyEgAf6BzO5d8TfH4vjDXjd18K0_BDDgRtaRuOv0cAvfLlm5O5rOY5uN9NXYIvLica-DbuHv7ijeCZFT-yNlDEdrRCm8QyfXtqMtnBev19Cmut4tdlw8pvwpR9qm2dyNl4t7dj9-I3F8T__5Rbc6IAoedOunNuwEao7cH2NnvAu5AdNe-maRGBL0HHEkLfANGmCnFaLol6Slvy4JqcV6QqbUNHk02mNxZptiec9OMrfftzZS7q-C4ljUukkBjGUKR63TyUCs5yn1KmJc9EbKF9aKoIOXsvCqswrpUURfYJ0qfRp4N5PNLsPm9V5FR4AKZ0TlnmrC5Zx7pyitGRWSu2Z85T6EbzqFWBcR0qOvTG-mT44iVNjmqkZwfNB9KJl4viT0MtGi4NEsTjD1LVMmM-zqZnTk8P5CZ2a_RFs92o2ndXWBuEkUo6xdATPhtfR3vASpajC-QplYgiGuFTEsTc6_ftozM40bx4e_rvoU7g6383N_rvZh0dwLcIz3iambcPmcrEKjyMEWtonzVL_CXzU_0I |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Methods+for+Compensating+Contrast+Effects+in+Information+Visualization&rft.jtitle=Computer+graphics+forum&rft.au=Mittelst%C3%A4dt%2C+S.&rft.au=Stoffel%2C+A.&rft.au=Keim%2C+D.+A.&rft.date=2014-06-01&rft.issn=0167-7055&rft.eissn=1467-8659&rft.volume=33&rft.issue=3&rft.spage=231&rft.epage=240&rft_id=info:doi/10.1111%2Fcgf.12379&rft.externalDBID=10.1111%252Fcgf.12379&rft.externalDocID=CGF12379 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0167-7055&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0167-7055&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0167-7055&client=summon |