Polarization fingerprint for microalgae classification
Involved Member: Dr. Meng YAN
A new method for classifying microalgae based on the physical properties encoded in the Mueller matrix is presented in the paper, which is a “polarization fingerprint” composed of sixteen polarization parameters that are selected based on their explicit physical meanings and associations with the structural properties of microalgae. Microalgae can be effectively classified by the polarization fingerprint and machine learning algorithms. This work demonstrates the potential of the polarization fingerprint to classify microalgae and monitor aquatic environments in-situ.
Reference: Li, J., Wei, J., Liu, H., Wan, J., Huang, T., Wang, H., Liao, R., Yan, M., Ma, H., (2023). Polarization fingerprint for microalgae classification. Optics and Lasers in Engineering, 166, 107567. (impact factor: 5.666)
