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Acta Armamentarii ›› 2023, Vol. 44 ›› Issue (7): 2122-2131.doi: 10.12382/bgxb.2022.0343

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Underwater Polarization Image Restoration Method Using Optimal Multi-Parameters Reconstruction

CHEN Xiongfeng1,2, RUAN Chi1,*()   

  1. 1 State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, Shaanxi, China
    2 University of the Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-05-06 Online:2023-07-30
  • Contact: RUAN Chi

Abstract:

Underwater imaging in high turbidity conditions often suffers from issues such as low resolution, reduced contrast, and overall poor image quality. Classical methods for underwater image polarization restoration require the selection of a background point without any target, making them inapplicable in certain scenarios. In order to solve this problem, the method of underwater polarization image restoration based on optimal multi-parameter reconstruction is proposed. Based on the classical underwater imaging physical model, the transmittance is divided into absorption and backscattering coefficients. By calculating the polarization degree of the underwater image using the Stokes vector, two target points are selected. The optimal reconstruction values of reflectivity, absorption coefficient and backscattering coefficient of two target points are obtained by optimizing the restored image. By using the optimized parameters to remove the backscattered light and recover the signal light lost due to absorption from the underwater image, the polarization restoration of the underwater image is realized. Two no-reference image quality assessment indexes are employed as quantitative indexes. Compared with other methods, experiments based on different turbidity and different targets show that this method can effectively restore the degraded underwater image, especially in the case of high turbidity. This method is expected to be applied to enhance optical imaging clarity of underwater vehicles and facilitate subsequent target detection.

Key words: underwater image restoration, polarization image, optimal reconstruction, multi-parameters