AUTHOR=Song Hong , Mehdi Syed Raza , Li Zixin , Wang Mengjie , Wu Chaopeng , Venediktov Vladimir Yu , Huang Hui TITLE=Investigating the rate of turbidity impact on underwater spectral reflectance detection JOURNAL=Frontiers in Marine Science VOLUME=Volume 10 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2023.1031869 DOI=10.3389/fmars.2023.1031869 ISSN=2296-7745 ABSTRACT=Spectral reflectance of the targeted object is considered a vital inherent optical property for its potential to provide abundant spectral information, which is crucial for object detection in underwater spectral imaging. However, the coarse condition of the underwater environment due to turbidity causes extreme errors in spectral reflectance detection because of the high absorption and scattering of light. To cope with the effects of light degradation on underwater spectral reflectance detection accuracy, the rate of the impacts of turbidity on spectral reflectance should be examined thoroughly. Therefore, we utilize a stare-type underwater spectral imaging system based on a liquid crystal tunable filter (LCTF) to experiment with the effects of varying turbidity in underwater spectral imaging of various colored bodies. To examine the accuracy of underwater spectral reflectance detection based on escalating turbidity, the paper models the rate of increase in scattering intensity of the water body. Results show that, based on the non-linear increase in the pixel response of the black and white board, the rapid upsurge in scattering intensity occurs between 400nm to 500nm at different turbidity levels. Furthermore, the spectral reconstruction of varying color blocks relative to the black and white board shows the maximum absolute deviation of 5.3% in spectral reflectance detection accuracy under varying turbidity conditions of the water body. While employing underwater spectral imaging, the above findings can find significant applications to improve the quality of underwater object detection.