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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.

The visualization of polarimetric data is often done by color mapping the linear parameters using the three channels in the HSV color space. Because this color space is not an accurate model of human color perception, the resulting visualization mixes the perceptual channels and contains nonuniformity. To the best of our knowledge, we present a new mapping strategy that reliably and accurately depicts reality by placing the polarization parameters directly into the perceptually uniform channels of CAM02-UCS. This mapping also ensures that regions of high polarization will be more visible, even when the measured irradiance is low.

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.