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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://doab-dev.siscern.org/handle/20.500.12854/169139
            Keywords
            Plenoptic; Light Field; Gigapixel; Multiview Stereposis; Plenoptic Imaging; Plenoptic Reconstruction; Computational Imaging; Visual Intelligence; Gigapixel Image Processing; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science::TGMT Testing of materials
            DOI
            10.1007/978-981-97-6915-5
            ISBN
            9789819769155, 9789819769148
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Singapore, 2025
            Imprint
            Springer Nature Singapore
            Series
            Advances in Computer Vision and Pattern Recognition,
            Pages
            389
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            Credits


            • logo Investir l'avenirInvestir l'avenir
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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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