Enhancement of underwater vision by fully exploiting the polarization information from the Stokes vector

Yi, Wei; Han, Peng; Liu, Fei; Shao, Xiaopeng

doi:10.1364/oe.433072

Cited by 42 publications

(17 citation statements)

References 24 publications

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“…the incident light has passed through one medium (Mueller matrix is M), the Stokes vector S of incident light will be changed to S ' [1,12]:…”

Section: Underwater Polarization Imaging Measurement Theorymentioning

confidence: 99%

“…Tian [11] has combined synthetic aperture imaging with polarimetric imaging and proposed a method for retrieving the radiation of an object based on the degree of polarization and intensity of backward scattering at the multi-view image. AMER [12] has used a polarimetric imaging optical system to reduce the effect of diffusion on the image acquisition and has received a great deal of attention for image dehazing based on an optimized version of the dark channel prior (DCP) method.…”

Section: Introductionmentioning

confidence: 99%

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Polarization Reconstruction Algorithm of Target Based on the Analysis of Noise in Complex Underwater Environment

et al. 2022

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How to effectively eliminate interference such as scattering, absorption, and attenuation is a hot topic of underwater photoelectric detection at present. Around the hot issues, this paper carries out studying the method of polarization-imaging recovery in a dynamic complex underwater environment from the theory of underwater radiation transfer, and numerical simulation of imaging interference characteristics to the simulation of underwater environment experiment. First, by conducting the analysis and simulation of scattering characteristics of underwater suspension particles and bubble by using the theory of radiation transfer, and taking advantage of quantitative description on changing tendency of radiation intensity and polarization properties of light waves in turbid water under the condition of scattering interference. Second, by constructing an underwater target polarization reconstruction model on the basis of the Mueller matrix analysis, and taking target polarization characteristic into reconstruction model on the basis of classical Schechner’s model, automatically estimating polarization information of target by the method of covariance. Finally, by building a polarization imaging system in the simulated complex underwater environment that contains bubble and suspended particles, obtaining reconstructed results with different underwater environments and different materials of target. According to experiment results, and compared with other traditional methods, using the proposed method in this paper can get higher resolution and higher contrast of target in the reconstructed result.

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“…the incident light has passed through one medium (Mueller matrix is M), the Stokes vector S of incident light will be changed to S ' [1,12]:…”

Section: Underwater Polarization Imaging Measurement Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Polarization Reconstruction Algorithm of Target Based on the Analysis of Noise in Complex Underwater Environment

et al. 2022

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“…In the existing polarization descattering model, it is especially important to estimate the degree of polarization (DoP) of target light and backscattered light accurately. However, most of the previous studies estimated the DoP of target light as a constant value because the full field of view (FOV) variation cannot be obtained [16], [17], [18]. In addition, according to the theory proposed by Treibitz et al [19], it is beneficial for reducing noise and achieving a better descattering imaging effect by increasing the difference between the DoP of target light and backscattered light, but so far it has been rarely focused.…”

Section: Introductionmentioning

confidence: 99%

Polarization Descattering Imaging of Underwater Complex Targets Based on Mueller Matrix Decomposition

Zhao

Ren

et al. 2022

IEEE Photonics J.

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The traditional polarization imaging techniques cannot obtain the polarization characteristics with global variation, and the reconstruction of the target with different optical properties concurrently is seriously distorted. In this work, we overcome the aforementioned shortcomings by using the polar decomposition method to estimate the Mueller matrix of the target in the full field of view. Simultaneously, the illumination light with globally varying polarization state is calculated to suppress the noise caused by computational imaging. The descattering imaging experiments through turbid water indicate that the images recovered by our method present the similarity to the targets without scattering, and the noise is suppressed to some extent. Further, we prove the superiority of the proposed method by comparing with other polarization underwater imaging strategies.

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“…Among them, the underwater polarization dehazing technology [5], [6], [7], [8] has been recognized as an effective method to obtain a clear dehazing image, due to the backscattering light being partially polarized [9], [10]. Many attempts have been made to improve the underwater polarization dehazing technology based on the Schechner's proposal by using the relationship between the object radiation and two orthogonal polarization images to realize the underwater image recovery [5], [9], such as the underwater polarimetric dehazing imaging model using the Stokes vectors to get polarization information [11], and the underwater image enhancement by using the wavelength compensation [12].…”

Section: Introductionmentioning

confidence: 99%

Underwater Polarization Imaging Recovery Based on Polarimetric Residual Dense Network

et al. 2022

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Application of deep-learning to polarization imaging technology for image restoration has led to many technological breakthroughs, especially in underwater image recovery and recognition. In this work, a four-input deep learning model with the Polarimetric Residual Dense Network is proposed for underwater image recovery. The diverse polarization component images are trained and tested in different processes in the network for the recognition and dehazing by considering the physical model of polarization dehazing imaging. Our study reveals that the proposed method can efficiently recover the hazed images, and provide good performance for improving the quality of image restoration even in a high-turbidity complex underwater environment.

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Enhancement of underwater vision by fully exploiting the polarization information from the Stokes vector

Cited by 42 publications

References 24 publications

Polarization Reconstruction Algorithm of Target Based on the Analysis of Noise in Complex Underwater Environment

Polarization Reconstruction Algorithm of Target Based on the Analysis of Noise in Complex Underwater Environment

Polarization Descattering Imaging of Underwater Complex Targets Based on Mueller Matrix Decomposition

Underwater Polarization Imaging Recovery Based on Polarimetric Residual Dense Network

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