Probing the suspended particles in natural water is significant for environmental monitoring and ecological research, such as early warning of water blooms and assessment of water quality. The particulate Mueller matrix polarimetry (PMP) based on polarized light scattering is established, which can be used to obtain the physical properties and polarization features of individual suspended particles in water. Previous researchers have measured the bulk Mueller matrix of water, in order to obtain information on suspended particles. However, there are many different suspended particles in the water, and the bulk Mueller matrix of water is difficult to know the properties of each particle and precisely retrieve the specific proportions of target suspended particles in the water. Recently, PMP can individually measure the suspended particles, and unlocks the potential of the Mueller matrix for the recognition and characterization of individual suspended particles in water. Powered by machine learning, many experimental results prove the potential abilities of PMP for the in-situ recognition and concentration proportions monitoring of different suspended particles in water.
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