Traditional imaging methods and computer vision algorithms are often ineffective when images are acquired in scattering media, such as underwater, fog, or biological tissue. Compared with the atmospheric scattering environment, densely underwater scattering modeling is more difficult. In this chapter, we introduce an underwater scattering image restoration and depth estimation algorithm based on light field imaging. First, we present a new single-image restoration algorithm which removes backscatter and attenuation from images better than existing methods, and we apply it to each view in the light field. Second, we combine a novel transmission-based depth cue with existing correspondence and defocus cues to improve light field depth estimation. In densely scattering media, our transmission depth cue is critical for depth estimation since the images have low signal-to-noise ratios which significantly degrades the performance of the correspondence and defocus cues. Finally, we propose shearing and refocusing multiple views of the light field to recover a single image of higher quality than what is possible from a single view. We demonstrate the benefits of our method through extensive experimental results in a water tank.


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    Titel :

    Underwater Descattering from Light Field


    Weitere Titelangaben:

    Research on Intelligent Manufacturing


    Beteiligte:
    Tian, Jiandong (Autor:in)


    Erscheinungsdatum :

    2021-12-02


    Format / Umfang :

    17 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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