User study comparing linearity and orthogonalization for polarimetric visualizations

Andrew W. Kruse, Damien J. Mannion, Andrey S. Alenin, J. Scott Tyo

Research output: Contribution to journalArticleResearchpeer-review


Traditionally, polarimetric imaging data is visualized by mapping angle of polarization, degree of polarization, and intensity to hue, saturation, and value coordinates of HSV color space. Due to possible perceptual uniformity issues in HSV, a method based on CAM02-UCS color space has been recently proposed. In this user study, the perceptual uniformity and nonlinear bias of the encoding of the degree of polarization parameter into the chromatic magnitude color channel is modeled by a power-law relationship between stimulus scale level and is estimated from responses to paired 2-alternative forced choice questions using Maximum Likelihood Difference Scaling. Estimated exponent and noise parameters for these methods are compared for same-hue and different-hue conditions to determine whether the chromatic magnitude channel can be used to orthogonality encode data parameters independently from the hue channel. Overall, the HSV condition displayed more nonuniformity, more nonlinear bias, and more non-orthogonality than the UCS condition. The results here indicate a lower bound for differences between methods since the intensity was chosen for the 'best case' of HSV. These results further support the claim that the chromatic magnitude color channel of a uniform color space can be used to encode a data parameter independently of the hue channel in a multivariate colormapping visualization.

Original languageEnglish
Pages (from-to)28308-28321
Number of pages14
JournalIEEE Access
Publication statusPublished - 4 Mar 2022
Externally publishedYes


  • color
  • data visualization
  • optical polarization
  • Polarimetry
  • psychometric testing
  • user centered design
  • visualization

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