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A Fourier Disparity Layer Representation for Light Fields.

Mikael Le Pendu, Christine Guillemot, Aljosa Smolic

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |June 21, 2019
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    Summary

    We introduce Fourier Disparity Layers (FDL), a novel Light Field representation for efficient processing and rendering. FDL enables real-time rendering and advanced applications like view interpolation and denoising.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Image Processing

    Background:

    • Light Field (LF) data captures 6D information, enabling novel rendering and post-capture refocusing.
    • Existing LF representations often face challenges in efficient processing and real-time rendering.

    Purpose of the Study:

    • To propose a new Light Field representation, Fourier Disparity Layers (FDL), for efficient processing and rendering.
    • To enable real-time rendering and facilitate direct applications like view interpolation and denoising.

    Main Methods:

    • Decomposing the Light Field into discrete layers sampled along the depth/disparity dimension.
    • Utilizing Fourier domain analysis for layer construction via regularized least squares regression.
    • Implementing a GPU-accelerated pipeline for efficient parallel processing.

    Main Results:

    • Achieved real-time Light Field rendering capabilities.
    • Demonstrated effective view interpolation, extrapolation, and denoising.
    • Developed a gradient descent-based calibration for optimal disparity estimation.

    Conclusions:

    • Fourier Disparity Layers (FDL) offer an efficient and versatile representation for Light Field data.
    • The proposed method enables high-quality, real-time rendering and advanced image manipulation.
    • FDL provides a robust framework for various Light Field applications.