Original data from a research for developing hue change phenomenon into mature quantitative analysis technique (including chemical imaging)

We proposed a novel hue descriptor (Huev) with a tunable hue quantification sequence via Hue Threshold (HT) to solve the problem that the hue quantification sequences of existing quantitative parameters are fixed and lack adaptability to diverse hue change sequences of multi-hue optical sensors. Then we systematically investigated how to correlate Huev with quantitative analysis (including chemical imaging) of multi-hue optical sensors, and developed a user-friendly analysis platform (composed of a machine vision device and an IQA software) to facilitate the application of this method. The wider applicability of Huev than existing parameters, and the practicability of this method in mean analyte concentration measurement and chemical imaging were proved. Raw data of the figures in main text and extended data were shown here. The structure and content of the dataset were presented in the README.txt file. This is the version 1.1 to correct the error of filenames in version 1.0. When comparing Huev with existing parameters, we used these parameters to analyze many sensor images from published literature. Snipaste software was used to cut sensor images from the literature downloaded in PDF format for further analysis. The titles of these literature were presented in the References section of this upload. Raw images of neutral litmus test strips, Pb test strips, and universal pH test strips used for calibration and accuracy experiments were also provided here. The executable (.exe) file of IQA software is provided here, which can be run independently on Windows system. The source code (developed by Python 3.8 64-bit) of IQA is available at https://github.com/Sun-haitao666/Source-code-of-IQA-software. The code of IQA is open source (MIT License). The method of using IQA was shown in the "Simple demonstration of using the IQA software.pdf" file.