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    Plenoptic Imaging and Processing

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    Author(s)
    Fang, Lu
    Language
    English
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    Abstract
    This open access book delves into the fundamental principles and cutting-edge techniques of plenoptic imaging and processing. Derived from the Latin words "plenus" (meaning "full") and "optic," plenoptic imaging offers a transformative approach to optical imaging. Unlike conventional systems that rely solely on the pinhole camera model to capture spatial information, plenoptic imaging aims to detect and reconstruct multidimensional and multiscale information from light rays in space. Chapter 1 begins with the introduction of the basic principle of the plenoptic function and the historical development of plenoptic imaging. Next, Chapter 2 describes representative plenoptic sensing systems, including single-sensor devices with lenslet arrays, coded-aperture masks, structured camera arrays, and unstructured camera arrays. Then, Chapter 3 introduces gigapixel plenoptic sensing techniques capable of capturing large-scale dynamic scenes with extremely high resolution. Further, chapter 4 examines typical plenoptic reconstruction methods, including light-field image reconstruction, image-based, and RGBD-based geometry reconstruction. After that, chapter 5 tackles the challenges of large-scale plenoptic reconstruction by introducing sparse-view priors, high-resolution observations, and semantic information. Finally, chapter 6 discusses the frontier issues of plenoptic processing, including the gigapixel-level video dataset PANDA and corresponding visual intelligent algorithms.
    URI
    https://library.oapen.org/handle/20.500.12657/94626
    Keywords
    Plenoptic; Light Field; Gigapixel; Multiview Stereposis; Plenoptic Imaging; Plenoptic Reconstruction; Computational Imaging; Visual Intelligence; Gigapixel Image Processing
    DOI
    10.1007/978-981-97-6915-5
    ISBN
    9789819769155, 9789819769148, 9789819769155
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Singapore, 2025
    Imprint
    Springer Nature Singapore
    Series
    Advances in Computer Vision and Pattern Recognition,
    Classification
    Computer vision
    Electronics engineering
    Image processing
    Testing of materials
    Pages
    389
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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