The method for mapping linear polarization imaging variables to the color channels of hue, saturation, and value in the HSV color space is a common technique for the visualization of polarization imaging data. This method utilizes the structural similarities between polarization vision and color vision so that the full linear polarization information is depicted in a single image. Recent developments have attempted to address issues, arising from the fact that the HSV color space is not an accurate model of human color vision, by mapping the polarization channels of intensity, degree, and angle to the color channels of lightness, colorfulness, and hue defined in the perceptually uniform color space CAM02-UCS. While the theoretical benefits of this method have been demonstrated using metrics of perceptual uniformity and channel independence, the practical benefits to human observers has not been studied. In this user study, the two methods are compared using a series of forced-choice questions on the perceived magnitude differences in DoLP value to determine 1) which method produces fewer errors, 2) which method produces a more linear scale in degree of polarization perception, 3) whether the perception of degree of polarization is independent of intensity and angle of polarization.
Collected sources for the different types of visualizations used in the field of polarization imaging are not extensive. Here, we survey and review the different visualization techniques in passive polarimetric imaging. Analysis of the methods is done by applying various concepts from the field of visualization. We provide recommendations for choosing a visualization based on the data structure, spatial frequency, and analysis goals.
Visualizing polarimetric imaging data is a difficult task due to its multidimensional nature, and there have been many different approaches to develop techniques for displaying this information. Currently, there is no method for producing effective visualizations, or evaluating their performance in accomplishing their intended goals. A task-based design process can be used to make sure that the unavoidable biases that occur in these visual representations match the biases required for effectively interpreting the information, relationships, and features within the data. As the field of polarimetric imaging grows and extends into other fields, some standardization of effective visualization techniques may be beneficial in communication and continued growth.
Current visualization techniques for mapping polarization data to a color coordinates defined by the Hue,
Saturation, Value (HSV) color representation are analyzed in the context of perceptual uniformity. Since HSV is
not designed to be perceptually uniform, the extent of non-uniformity should be evaluated by using robust color
difference formulae and by comparison to the state-of-the-art uniform color space CAM02-UCS. For mapping just
angle of polarization with HSV hue, the results show clear non-uniformity and implications for how this can
misrepresent the data. UCS can be used to create alternative mapping techniques that are perceptually uniform.
Implementing variation in lightness may increase shape discrimination within the scene. Future work will be
dedicated to measuring performance of both current and proposed methods using psychophysical analysis.