Plug-and-Play for Joint Deblurring and Guided Super-Resolution of Single-Photon 3D Lidar data

Abderrahim Halimi; Stephen McLaughlin

doi:10.23919/eusipco58844.2023.10289913

Plug-and-Play for Joint Deblurring and Guided Super-Resolution of Single-Photon 3D Lidar data

Abderrahim Halimi, Stephen McLaughlin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

This paper presents a new method for joint deblurring and super-resolution of 3D single-photon Lidar images. Adopting a plug-and-play framework, the method alternates between a data fidelity iterate, and a guided filtering (GF) step which can be performed by any existing GF algorithm. The resulting analytical updates are efficient and are easily adapted to different upscaling factors or arbitrary blur kernels. Thanks to the GF algorithm, the algorithm shows good denoising performance when imaging in extreme conditions leading to high background noise. Experiments on simulated and real data demonstrate the good performance of the proposed strategy in terms of depth maps deblurring and super-resolution in presence of high levels of noise.

Original language	English
Title of host publication	31st European Signal Processing Conference (EUSIPCO 2023)
Publisher	IEEE
Pages	1718-1722
Number of pages	5
ISBN (Electronic)	9789464593600
DOIs	https://doi.org/10.23919/eusipco58844.2023.10289913
Publication status	Published - 1 Nov 2023
Event	31st European Signal Processing Conference 2023 - Helsinki, Finland Duration: 4 Sept 2023 → 8 Sept 2023 https://eusipco2023.org/ http://eusipco2023.org/

Conference

Conference	31st European Signal Processing Conference 2023
Abbreviated title	EUSIPCO 2023
Country/Territory	Finland
City	Helsinki
Period	4/09/23 → 8/09/23
Internet address	https://eusipco2023.org/ http://eusipco2023.org/

Keywords

3D Reconstruction
Deblurring
Lidar
Plug-and-PLay
Single-Photon Imaging
Super-Resolution

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering

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10.23919/eusipco58844.2023.10289913

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Cite this

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title = "Plug-and-Play for Joint Deblurring and Guided Super-Resolution of Single-Photon 3D Lidar data",

abstract = "This paper presents a new method for joint deblurring and super-resolution of 3D single-photon Lidar images. Adopting a plug-and-play framework, the method alternates between a data fidelity iterate, and a guided filtering (GF) step which can be performed by any existing GF algorithm. The resulting analytical updates are efficient and are easily adapted to different upscaling factors or arbitrary blur kernels. Thanks to the GF algorithm, the algorithm shows good denoising performance when imaging in extreme conditions leading to high background noise. Experiments on simulated and real data demonstrate the good performance of the proposed strategy in terms of depth maps deblurring and super-resolution in presence of high levels of noise. ",

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booktitle = "31st European Signal Processing Conference (EUSIPCO 2023)",

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note = "31st European Signal Processing Conference 2023, EUSIPCO 2023 ; Conference date: 04-09-2023 Through 08-09-2023",

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Y1 - 2023/11/1

N2 - This paper presents a new method for joint deblurring and super-resolution of 3D single-photon Lidar images. Adopting a plug-and-play framework, the method alternates between a data fidelity iterate, and a guided filtering (GF) step which can be performed by any existing GF algorithm. The resulting analytical updates are efficient and are easily adapted to different upscaling factors or arbitrary blur kernels. Thanks to the GF algorithm, the algorithm shows good denoising performance when imaging in extreme conditions leading to high background noise. Experiments on simulated and real data demonstrate the good performance of the proposed strategy in terms of depth maps deblurring and super-resolution in presence of high levels of noise.

AB - This paper presents a new method for joint deblurring and super-resolution of 3D single-photon Lidar images. Adopting a plug-and-play framework, the method alternates between a data fidelity iterate, and a guided filtering (GF) step which can be performed by any existing GF algorithm. The resulting analytical updates are efficient and are easily adapted to different upscaling factors or arbitrary blur kernels. Thanks to the GF algorithm, the algorithm shows good denoising performance when imaging in extreme conditions leading to high background noise. Experiments on simulated and real data demonstrate the good performance of the proposed strategy in terms of depth maps deblurring and super-resolution in presence of high levels of noise.

KW - 3D Reconstruction

KW - Deblurring

KW - Lidar

KW - Plug-and-PLay

KW - Single-Photon Imaging

KW - Super-Resolution

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M3 - Conference contribution

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EP - 1722

BT - 31st European Signal Processing Conference (EUSIPCO 2023)

PB - IEEE

T2 - 31st European Signal Processing Conference 2023

Y2 - 4 September 2023 through 8 September 2023

ER -

Plug-and-Play for Joint Deblurring and Guided Super-Resolution of Single-Photon 3D Lidar data

Abstract

Conference

Keywords

ASJC Scopus subject areas

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