BM3D Filtering Algorithm for DoFP Polarization Image Sensors

Abubakar Abubakar, Xiaojin Zhao, Maen Takruri, Eesa Bastaki, Amine Bermak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a Block Matching and 3D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization image sensors. This method, based on grouping and a non-local filtering method named collaborative filtering, exploits all the different polarization channels simultaneously. Extensive experimental results on the test images show that the algorithm outperforms a wide range of existing denoising algorithms for DoFP images including the state-of-the-art principal component analysis (PCA) based denoising algorithm visually by preserving more details, as well as in terms of Peak-Signal-to-Noise-Ratio (PSNR).

Original languageEnglish
Title of host publication2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538668115
DOIs
Publication statusPublished - 31 Jan 2019
Event23rd IEEE International Conference on Digital Signal Processing, DSP 2018 - Shanghai, China
Duration: 19 Nov 201821 Nov 2018

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2018-November

Conference

Conference23rd IEEE International Conference on Digital Signal Processing, DSP 2018
CountryChina
CityShanghai
Period19/11/1821/11/18

Fingerprint

Image sensors
Polarization
Collaborative filtering
Principal component analysis
Signal to noise ratio

ASJC Scopus subject areas

  • Signal Processing

Cite this

Abubakar, A., Zhao, X., Takruri, M., Bastaki, E., & Bermak, A. (2019). BM3D Filtering Algorithm for DoFP Polarization Image Sensors. In 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018 [8631582] (International Conference on Digital Signal Processing, DSP; Vol. 2018-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDSP.2018.8631582

BM3D Filtering Algorithm for DoFP Polarization Image Sensors. / Abubakar, Abubakar; Zhao, Xiaojin; Takruri, Maen; Bastaki, Eesa; Bermak, Amine.

2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8631582 (International Conference on Digital Signal Processing, DSP; Vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abubakar, A, Zhao, X, Takruri, M, Bastaki, E & Bermak, A 2019, BM3D Filtering Algorithm for DoFP Polarization Image Sensors. in 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018., 8631582, International Conference on Digital Signal Processing, DSP, vol. 2018-November, Institute of Electrical and Electronics Engineers Inc., 23rd IEEE International Conference on Digital Signal Processing, DSP 2018, Shanghai, China, 19/11/18. https://doi.org/10.1109/ICDSP.2018.8631582
Abubakar A, Zhao X, Takruri M, Bastaki E, Bermak A. BM3D Filtering Algorithm for DoFP Polarization Image Sensors. In 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018. Institute of Electrical and Electronics Engineers Inc. 2019. 8631582. (International Conference on Digital Signal Processing, DSP). https://doi.org/10.1109/ICDSP.2018.8631582
Abubakar, Abubakar ; Zhao, Xiaojin ; Takruri, Maen ; Bastaki, Eesa ; Bermak, Amine. / BM3D Filtering Algorithm for DoFP Polarization Image Sensors. 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018. Institute of Electrical and Electronics Engineers Inc., 2019. (International Conference on Digital Signal Processing, DSP).
@inproceedings{bc8a5915f8b5475e866a20ce2fae5750,
title = "BM3D Filtering Algorithm for DoFP Polarization Image Sensors",
abstract = "In this paper, we present a Block Matching and 3D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization image sensors. This method, based on grouping and a non-local filtering method named collaborative filtering, exploits all the different polarization channels simultaneously. Extensive experimental results on the test images show that the algorithm outperforms a wide range of existing denoising algorithms for DoFP images including the state-of-the-art principal component analysis (PCA) based denoising algorithm visually by preserving more details, as well as in terms of Peak-Signal-to-Noise-Ratio (PSNR).",
author = "Abubakar Abubakar and Xiaojin Zhao and Maen Takruri and Eesa Bastaki and Amine Bermak",
year = "2019",
month = "1",
day = "31",
doi = "10.1109/ICDSP.2018.8631582",
language = "English",
series = "International Conference on Digital Signal Processing, DSP",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018",

}

TY - GEN

T1 - BM3D Filtering Algorithm for DoFP Polarization Image Sensors

AU - Abubakar, Abubakar

AU - Zhao, Xiaojin

AU - Takruri, Maen

AU - Bastaki, Eesa

AU - Bermak, Amine

PY - 2019/1/31

Y1 - 2019/1/31

N2 - In this paper, we present a Block Matching and 3D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization image sensors. This method, based on grouping and a non-local filtering method named collaborative filtering, exploits all the different polarization channels simultaneously. Extensive experimental results on the test images show that the algorithm outperforms a wide range of existing denoising algorithms for DoFP images including the state-of-the-art principal component analysis (PCA) based denoising algorithm visually by preserving more details, as well as in terms of Peak-Signal-to-Noise-Ratio (PSNR).

AB - In this paper, we present a Block Matching and 3D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization image sensors. This method, based on grouping and a non-local filtering method named collaborative filtering, exploits all the different polarization channels simultaneously. Extensive experimental results on the test images show that the algorithm outperforms a wide range of existing denoising algorithms for DoFP images including the state-of-the-art principal component analysis (PCA) based denoising algorithm visually by preserving more details, as well as in terms of Peak-Signal-to-Noise-Ratio (PSNR).

UR - http://www.scopus.com/inward/record.url?scp=85062801528&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062801528&partnerID=8YFLogxK

U2 - 10.1109/ICDSP.2018.8631582

DO - 10.1109/ICDSP.2018.8631582

M3 - Conference contribution

T3 - International Conference on Digital Signal Processing, DSP

BT - 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -