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Layered Light Field Reconstruction for Defocus Blur

Published: 02 March 2015 Publication History

Abstract

We present a novel algorithm for reconstructing high-quality defocus blur from a sparsely sampled light field. Our algorithm builds upon recent developments in the area of sheared reconstruction filters and significantly improves reconstruction quality and performance. While previous filtering techniques can be ineffective in regions with complex occlusion, our algorithm handles such scenarios well by partitioning the input samples into depth layers. These depth layers are filtered independently and then combined together, taking into account inter-layer visibility. We also introduce a new separable formulation of sheared reconstruction filters that achieves real-time preformance on a modern GPU and is more than two orders of magnitude faster than previously published techniques.

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Cited By

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  • (2024)Impact of focus cue presentation on perceived realism of 3-D scene structure: Implications for scene perception and for display technologyJournal of Vision10.1167/jov.24.2.1324:2(13)Online publication date: 27-Feb-2024
  • (2023)A 250-mW 5.4G-Rendered-Pixel/s Realistic Refocusing Processor for High-Performance Five-Camera Mobile DevicesIEEE Open Journal of the Solid-State Circuits Society10.1109/OJSSCS.2023.32447593(52-62)Online publication date: 2023
  • (2023)Robust extension of light fields with probable 3D distribution based on iterative scene estimation from multi-focus imagesSignal Processing: Image Communication10.1016/j.image.2022.116896111(116896)Online publication date: Feb-2023
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Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 34, Issue 2
February 2015
136 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/2742222
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 02 March 2015
Received: 01 October 2014
Accepted: 01 September 2014
Revised: 01 August 2014
Published in TOG Volume 34, Issue 2

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Author Tags

  1. Depth of field
  2. Fourier analysis
  3. defocus blur
  4. light field reconstruction
  5. reconstruction

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Cited By

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  • (2024)Impact of focus cue presentation on perceived realism of 3-D scene structure: Implications for scene perception and for display technologyJournal of Vision10.1167/jov.24.2.1324:2(13)Online publication date: 27-Feb-2024
  • (2023)A 250-mW 5.4G-Rendered-Pixel/s Realistic Refocusing Processor for High-Performance Five-Camera Mobile DevicesIEEE Open Journal of the Solid-State Circuits Society10.1109/OJSSCS.2023.32447593(52-62)Online publication date: 2023
  • (2023)Robust extension of light fields with probable 3D distribution based on iterative scene estimation from multi-focus imagesSignal Processing: Image Communication10.1016/j.image.2022.116896111(116896)Online publication date: Feb-2023
  • (2022)Spectral analysis of a surface occlusion model for image-based rendering samplingDigital Signal Processing10.1016/j.dsp.2022.103697130(103697)Online publication date: Oct-2022
  • (2020)Neural Denoising with Layer EmbeddingsComputer Graphics Forum10.1111/cgf.1404939:4(1-12)Online publication date: 20-Jul-2020
  • (2020)Image Synthesis With Efficient Defocus Blur for Stereoscopic DisplaysIEEE Access10.1109/ACCESS.2020.30263328(176304-176312)Online publication date: 2020
  • (2019)Multiagent Light Field Reconstruction and Maneuvering Target Recognition via GANMathematical Problems in Engineering10.1155/2019/97109742019:1Online publication date: 24-Dec-2019
  • (2018)Laplacian kernel splatting for efficient depth-of-field and motion blur synthesis or reconstructionACM Transactions on Graphics10.1145/3197517.320137937:4(1-11)Online publication date: 30-Jul-2018
  • (2018)Structure Models for Image-Assisted Geometry Measurement in Plenoptic SamplingIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2017.275595867:1(150-166)Online publication date: Jan-2018
  • (2017)Spatiotemporal variance-guided filteringProceedings of High Performance Graphics10.1145/3105762.3105770(1-12)Online publication date: 28-Jul-2017
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