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Journal ArticleDOI

6-DOF motion blur synthesis and performance evaluation of light field deblurring

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TLDR
The experiment results show that the proposed blur model can maintain the parallax information (depth-dependent blur) in a light field image and produce a synthetic blurry light field dataset based on the 6-DOF model.
Abstract
Motion deblurring is essential for reconstructing sharp images from given a blurry input caused by the camera motion. The complexity of this problem increases in a light field due to its depth-dependent blur constraint. A method of generating synthetic 3 degree-of-freedom (3-DOF) translation blur on a light field image without camera rotation has been introduced. In this study, we generate a camera translation and rotation (6-DOF) motion blur model that preserves the consistency of the light field image. Our experiment results show that the proposed blur model can maintain the parallax information (depth-dependent blur) in a light field image. Furthermore, we produce a synthetic blurry light field dataset based on the 6-DOF model. Finally, to validate the usability of the synthetic dataset, we conduct extensive benchmarking using state-of-the-art motion deblurring algorithms.

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Citations
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Journal ArticleDOI

View Adaptive Light Field Deblurring Networks with Depth Perception

TL;DR: Zhang et al. as mentioned in this paper designed a view adaptive spatial convolution to deblur blurred LFs, which calculates the exclusive convolution kernel for each view and introduces an angular position embedding to maintain the light field structure better.
Journal ArticleDOI

Artistic Expression in Visual Communication Design in Multimedia Background

TL;DR: In this paper , the authors analyzed the role and influence of current artistic elements on visual communication design in the multimedia environment, and they drew on the principles and laws of visual communication to analyze and evaluate image processing techniques.
References
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Proceedings ArticleDOI

Image and depth from a conventional camera with a coded aperture

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Journal ArticleDOI

Fast motion deblurring

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Book ChapterDOI

Two-phase kernel estimation for robust motion deblurring

TL;DR: It is found that strong edges do not always profit kernel estimation, but instead under certain circumstance degrade it, which leads to a new metric to measure the usefulness of image edges in motion deblurring and a gradient selection process to mitigate their possible adverse effect.
Proceedings ArticleDOI

Blind deconvolution using a normalized sparsity measure

TL;DR: A new type of image regularization which gives lowest cost for the true sharp image is introduced, which allows a very simple cost formulation to be used for the blind deconvolution model, obviating the need for additional methods.
Proceedings ArticleDOI

Unnatural L0 Sparse Representation for Natural Image Deblurring

TL;DR: This paper proposes a generalized and mathematically sound L0 sparse expression, together with a new effective method, for motion deblurring that does not require extra filtering during optimization and demonstrates fast energy decreasing, making a small number of iterations enough for convergence.
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