Periodic integration-based polarization differential imaging for underwater image restoration
•A PDI method is proposed to obtain the polarization differential image by accumulating the polarization images in the dimension of polarization direction.•The proposed method can effectively eliminate the interference caused by the inconsistent AOP of reflected light and can suppress image noise.•T...
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Veröffentlicht in: | Optics and lasers in engineering 2022-02, Vol.149, p.106785, Article 106785 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A PDI method is proposed to obtain the polarization differential image by accumulating the polarization images in the dimension of polarization direction.•The proposed method can effectively eliminate the interference caused by the inconsistent AOP of reflected light and can suppress image noise.•The underwater image restoration experiments demonstrate that the proposed method performs better in terms of differential image acquisition and image noise suppression.
Underwater image restoration is extensively used in many applications, such as ocean exploration and underwater rescue. With the development of polarization imaging technology, polarization differential imaging (PDI) has gradually become one of the most effective tools for image restoration in the underwater environment. To eliminate the interferences of inconsistent polarization direction and image noise in conventional PDI systems, we propose a new underwater image restoration method based on the periodic integration of polarization images. The method replaces one or two pairs of orthogonal polarization images with the integration of a series of polarization images in PDI system to achieve underwater image restoration. Firstly, we captured a series of polarization images in different polarization directions during a complete variation cycle of image intensity. Then, these polarization images are accumulated together, and the result is approximately regarded as the intensity integration of polarization light in the dimension of polarization direction. Finally, we can calculate the polarization degree of each pixel and obtain a clear polarization differential image. Compared with the existing PDI methods based on one or two pairs of orthogonal polarization images, both qualitative and quantitative experimental results show that the proposed method has better performance in texture enhancement and noise suppression. |
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ISSN: | 0143-8166 1873-0302 |
DOI: | 10.1016/j.optlaseng.2021.106785 |