The present application relates to the technical field of
image processing, and discloses a kind of polarization filtering and
light field imaging's
underwater alum flower identification method and
system, solve the problem that prior art cannot realize the high-fidelity acquisition and accurate quantification of
alum flower morphological characteristics under high
turbidity, dynamic
water quality working condition.The present application is through the collaborative optical design of polarization filtering and
light field imaging, suppresses water backscattering and
Mie scattering interference at the collection source, provides high-fidelity image basis for subsequent morphological quantification;Introduce double-domain
Gaussian window
spectrum shaping and truncated sinc interpolation kernel, improve the refocusing position accuracy without hardware modification, eliminate the
ringing artifact and
phase distortion caused by traditional linear interpolation;Multi-scale Retinex enhancement model accurately adapts to the
low contrast and multi-scale texture characteristics of
alum flower, retains the texture information required for fractal dimension calculation completely under the premise of avoiding
noise amplification, and
linear fitting is combined with box counting method, so that the fractal dimension
estimation error is reduced.