Hue Tinting for Interactive Data Visualization

'Hue tinting' is one of several user interaction techniques described that minimize typical problems with using false color visualizations. 'Hue tinting' interactions address the problem of how to best choose colors to show numbers while 1) using hue to mark only relevant aspects of the data and 2) minimizing color-related problems such as brightness distortion. Most visualization systems make it difficult to use hue variation to identify and compare features in a dataset without distorting the ordered mapping of quantity to brightness variation that encodes the relationships between the data's distributions. Like colorizing a black-and-white photograph, 'Hue tinting' lets you use hue to select, identify, and mark relevant portions of your data without distorting the brightness of the underlying grayscale visualization. Hue tinting a specific range of data values provides a direct method for validating and compliance-testing. Hue tinting a specific region of an image provides a direct method for identifying and measuring features in a dataset, such as the range of power levels within a given range of frequencies. Hue tinting and the other user interactions on false-color visualizations described here can be applied directly to low-level tasks such as identification and comparison without introducing brightness distortions that complicate high-level tasks such as understanding the distributions of values with respect to each other. Datasets, visualization types, and associated tasks are chosen from the field of electronic measurement.