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Robust Rayleigh Reg...
Robust Rayleigh Regression Method for SAR Image Processing in Presence of Outliers
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- Palm, Bruna (författare)
- Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
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- Bayer, Fabio M. (författare)
- Univ Fed Santa Maria, BRA
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- Machado, Renato (författare)
- Aeronaut Inst Technol ITA, BRA
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- Pettersson, Mats, 1966- (författare)
- Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
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- Vu, Viet Thuy, 1977- (författare)
- Blekinge Tekniska Högskola,Institutionen för matematik och naturvetenskap
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- Cintra, Renato J. (författare)
- Univ Fed Pernambuco, BRA
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2022
- 2022
- Engelska.
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Ingår i: IEEE Transactions on Geoscience and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 0196-2892 .- 1558-0644. ; 60
- Relaterad länk:
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https://doi.org/10.1...
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https://bth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The presence of outliers (anomalous values) in synthetic aperture radar (SAR) data and the misspecification in statistical image models may result in inaccurate inferences. To avoid such issues, the Rayleigh regression model based on a robust estimation process is proposed as a more realistic approach to model this type of data. This article aims at obtaining Rayleigh regression model parameter estimators robust to the presence of outliers. The proposed approach considered the weighted maximum likelihood method and was submitted to numerical experiments using simulated and measured SAR images. Monte Carlo simulations were employed for the numerical assessment of the proposed robust estimator performance in finite signal lengths, their sensitivity to outliers, and the breakdown point. For instance, the nonrobust estimators show a relative bias value 65-fold larger than the results provided by the robust approach in corrupted signals. In terms of sensitivity analysis and break down point, the robust scheme resulted in a reduction of about 96% and 10%, respectively, in the mean absolute value of both measures, in compassion to the nonrobust estimators. Moreover, two SAR datasets were used to compare the ground type and anomaly detection results of the proposed robust scheme with competing methods in the literature. © 2022 IEEE.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Nyckelord
- Radar polarimetry
- Maximum likelihood estimation
- Synthetic aperture radar
- Data models
- Maximum likelihood detection
- Tools
- Numerical models
- Outliers
- Rayleigh regression model
- robust estimation
- synthetic aperture radar (SAR) images
- MODEL
- CLASSIFICATION
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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