Abstract

The absorption and scattering of impurity particles in turbid water cause the target signal light to be attenuated and to produce backscattered light, resulting in the reduced quality of underwater polarimetric imaging. As water turbidity increases, the effect of backscattered light becomes greater, making polarization imaging in highly turbid water a challenge. Theory and experiment show that the increase in the intensity of backscattered light leads to high noise gain in the underwater active polarization imaging model. In order to enhance image contrast and suppress noise gain in highly turbid water, we propose an underwater imaging enhancement method that appropriately combines the non-physical and physical models. The method uses contrast limited adaptive histogram equalization (CLAHE) for a certain number of cross-linear images (Imin) before calculating their polarization enhancement images, and it constructs joint filtering (multi-frame averaging and bilateral filtering) to suppress the high noise gain introduced by the imaging model and CLAHE. The experimental results in highly turbid water validate the rationality and feasibility of the proposed method, and the comparative processing results (52.7~98.6 NTU) outperform those of the conventional non-physical and physical model methods. The method maintains the complexity of the system and facilitates the application of conventional polarimetric imaging in harsher underwater environments.

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