Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing

Linhai Jia; Weidong Hu; Zhiyan Feng; Minghao Feng; Leo Ligthart

doi:10.1109/CSRSWTC60855.2023.10427545

Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing

Linhai Jia, Weidong Hu, Zhiyan Feng, Minghao Feng, Leo Ligthart

School of Integrated Circuits and Electronics

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

Abstract

Microwave radiometer Imager (MWRI) is widely applied in atmospheric remote sensing, and spatial resolution enhancement technique is ubiquitously taken to improve the quality of image data. In this paper, two deconvolution methods, the Wiener algorithm and Lucy-Richardson algorithm, are applied to deconvolute and denoise the antenna measurement image, which is simulated with parameter of MWRI on FY-3 Satellite. Result shows that in these two methods, Wiener method performs better in noise elimination, and Lucy-Richardson method performs better in spatial resolution and image relative coefficient. This helps the method selection in real project condition.

Original language	English
Title of host publication	Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350358971
DOIs	https://doi.org/10.1109/CSRSWTC60855.2023.10427545
Publication status	Published - 2023
Event	2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023 - Guilin, China Duration: 10 Nov 2023 → 13 Nov 2023

Publication series

Name	Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

Conference

Conference	2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023
Country/Territory	China
City	Guilin
Period	10/11/23 → 13/11/23

Keywords

deconvolution method
denoise
remote sensing
resolution enhancement

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10.1109/CSRSWTC60855.2023.10427545

Cite this

Jia, L., Hu, W., Feng, Z., Feng, M., & Ligthart, L. (2023). Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing. In Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023 (Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSRSWTC60855.2023.10427545

Jia, Linhai ; Hu, Weidong ; Feng, Zhiyan et al. / Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing. Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023).

@inproceedings{103be066d0634cf4b9a20e3790661040,

title = "Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing",

abstract = "Microwave radiometer Imager (MWRI) is widely applied in atmospheric remote sensing, and spatial resolution enhancement technique is ubiquitously taken to improve the quality of image data. In this paper, two deconvolution methods, the Wiener algorithm and Lucy-Richardson algorithm, are applied to deconvolute and denoise the antenna measurement image, which is simulated with parameter of MWRI on FY-3 Satellite. Result shows that in these two methods, Wiener method performs better in noise elimination, and Lucy-Richardson method performs better in spatial resolution and image relative coefficient. This helps the method selection in real project condition.",

keywords = "deconvolution method, denoise, remote sensing, resolution enhancement",

author = "Linhai Jia and Weidong Hu and Zhiyan Feng and Minghao Feng and Leo Ligthart",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023 ; Conference date: 10-11-2023 Through 13-11-2023",

year = "2023",

doi = "10.1109/CSRSWTC60855.2023.10427545",

language = "English",

series = "Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023",

address = "United States",

}

Jia, L, Hu, W, Feng, Z, Feng, M & Ligthart, L 2023, Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing. in Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023. Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023, Institute of Electrical and Electronics Engineers Inc., 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023, Guilin, China, 10/11/23. https://doi.org/10.1109/CSRSWTC60855.2023.10427545

Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing. / Jia, Linhai; Hu, Weidong; Feng, Zhiyan et al.
Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023).

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

TY - GEN

T1 - Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing

AU - Jia, Linhai

AU - Hu, Weidong

AU - Feng, Zhiyan

AU - Feng, Minghao

AU - Ligthart, Leo

PY - 2023

Y1 - 2023

N2 - Microwave radiometer Imager (MWRI) is widely applied in atmospheric remote sensing, and spatial resolution enhancement technique is ubiquitously taken to improve the quality of image data. In this paper, two deconvolution methods, the Wiener algorithm and Lucy-Richardson algorithm, are applied to deconvolute and denoise the antenna measurement image, which is simulated with parameter of MWRI on FY-3 Satellite. Result shows that in these two methods, Wiener method performs better in noise elimination, and Lucy-Richardson method performs better in spatial resolution and image relative coefficient. This helps the method selection in real project condition.

AB - Microwave radiometer Imager (MWRI) is widely applied in atmospheric remote sensing, and spatial resolution enhancement technique is ubiquitously taken to improve the quality of image data. In this paper, two deconvolution methods, the Wiener algorithm and Lucy-Richardson algorithm, are applied to deconvolute and denoise the antenna measurement image, which is simulated with parameter of MWRI on FY-3 Satellite. Result shows that in these two methods, Wiener method performs better in noise elimination, and Lucy-Richardson method performs better in spatial resolution and image relative coefficient. This helps the method selection in real project condition.

KW - deconvolution method

KW - denoise

KW - remote sensing

KW - resolution enhancement

UR - http://www.scopus.com/inward/record.url?scp=85186495247&partnerID=8YFLogxK

U2 - 10.1109/CSRSWTC60855.2023.10427545

DO - 10.1109/CSRSWTC60855.2023.10427545

M3 - Conference contribution

AN - SCOPUS:85186495247

T3 - Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

BT - Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

Y2 - 10 November 2023 through 13 November 2023

ER -

Jia L, Hu W, Feng Z, Feng M, Ligthart L. Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing. In Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings - 2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023). doi: 10.1109/CSRSWTC60855.2023.10427545

Research on Denoising Ability of Deconvolution Methods in Microwave Atmospheric Remote Sensing

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