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Polarized image enhancement based on biological vision

For passive polarization detection, limited by the scattering medium and the sensitivity of the detector, the detector usually can only receive the polarization information of the weak target. Moreover, nonlinear operators usually amplify the influence of noise in polarization parameter images. These factors result in low SNR of polarization images, which affects the application of polarization technology in different fields. This paper proposes a polarization image layering algorithm based on the principle of biological vision, which uses the statistical characteristics of the angle of polarization (AoP) as the weight parameter to perform contrast enhancement and denoising operations on the degree of polarization (DoP) image. And the final result can be obtained by simple fusion. Experimental results demonstrate that the algorithm is capable of improving the DOP of the target while suppressing background noise, which may provide new ideas for the application of polarized target detection and polarization visualization in interdisciplinary fields.