A Unitary Transformation Extension of PolSAR Four-Component Target Decomposition.
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| Title: | A Unitary Transformation Extension of PolSAR Four-Component Target Decomposition. |
|---|---|
| Authors: | Wang, Tingting1,2 (AUTHOR), Suo, Zhiyong1 (AUTHOR) zysuo@xidian.edu.cn, Ti, Jingjing1 (AUTHOR), Yan, Boya3 (AUTHOR), Xiang, Hongli2 (AUTHOR), Xi, Jiabao1 (AUTHOR) |
| Source: | Remote Sensing. Mar2024, Vol. 16 Issue 6, p1067. 25p. |
| Subjects: | Unitary transformations, Jacobi method, T-matrix, Decomposition method, Matrix decomposition |
| Abstract: | As an improvement on the traditional model-based Yamaguchi four-component decomposition method, in recent years, to fully utilize the polarization information in the coherency matrix, four-component target decomposition methods Y4R and S4R have been proposed, which are based on the rotation of the coherency matrix and the expansion of the volume model, respectively. At the same time, there is also an improved G4U method proposed based on Y4R and S4R. Although these methods have achieved certain decomposition results, there are still problems with overestimation of volume scattering and insufficient utilization of polarization information. In this paper, a unitary transformation extension to the four-component target decomposition method of PolSAR based on the properties of the Jacobi method is proposed. By analyzing the terms in the basic scattering models, such as volume scattering, in the existing four-component decomposition methods, it is clear that the reason for the existence of the residual matrix in the existing decomposition methods is that the off-diagonal term T 13 and the real part of T 23 of the coherency matrix T do not participate in the four-component decomposition. On this basis, a matrix transformation method is proposed to decouple terms T 13 and Re T 23 , and the residual matrix decomposed based on this method is derived. The performance of the proposed method was validated and evaluated using two datasets. The experimental results indicate that, compared with model-based methods such as Y4R, S4R and G4U, the proposed method can enhance the contribution of double-bounce scattering and odd-bounce scattering power in urban areas in both sets of data. The computational time of the proposed method is equivalent to Y4R, S4R, etc. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 176366638 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Unitary Transformation Extension of PolSAR Four-Component Target Decomposition. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Tingting%22">Wang, Tingting</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Suo%2C+Zhiyong%22">Suo, Zhiyong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zysuo@xidian.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ti%2C+Jingjing%22">Ti, Jingjing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Boya%22">Yan, Boya</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiang%2C+Hongli%22">Xiang, Hongli</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xi%2C+Jiabao%22">Xi, Jiabao</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Mar2024, Vol. 16 Issue 6, p1067. 25p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Unitary+transformations%22">Unitary transformations</searchLink><br /><searchLink fieldCode="DE" term="%22Jacobi+method%22">Jacobi method</searchLink><br /><searchLink fieldCode="DE" term="%22T-matrix%22">T-matrix</searchLink><br /><searchLink fieldCode="DE" term="%22Decomposition+method%22">Decomposition method</searchLink><br /><searchLink fieldCode="DE" term="%22Matrix+decomposition%22">Matrix decomposition</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As an improvement on the traditional model-based Yamaguchi four-component decomposition method, in recent years, to fully utilize the polarization information in the coherency matrix, four-component target decomposition methods Y4R and S4R have been proposed, which are based on the rotation of the coherency matrix and the expansion of the volume model, respectively. At the same time, there is also an improved G4U method proposed based on Y4R and S4R. Although these methods have achieved certain decomposition results, there are still problems with overestimation of volume scattering and insufficient utilization of polarization information. In this paper, a unitary transformation extension to the four-component target decomposition method of PolSAR based on the properties of the Jacobi method is proposed. By analyzing the terms in the basic scattering models, such as volume scattering, in the existing four-component decomposition methods, it is clear that the reason for the existence of the residual matrix in the existing decomposition methods is that the off-diagonal term T 13 and the real part of T 23 of the coherency matrix T do not participate in the four-component decomposition. On this basis, a matrix transformation method is proposed to decouple terms T 13 and Re T 23 , and the residual matrix decomposed based on this method is derived. The performance of the proposed method was validated and evaluated using two datasets. The experimental results indicate that, compared with model-based methods such as Y4R, S4R and G4U, the proposed method can enhance the contribution of double-bounce scattering and odd-bounce scattering power in urban areas in both sets of data. The computational time of the proposed method is equivalent to Y4R, S4R, etc. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs16061067 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 1067 Subjects: – SubjectFull: Unitary transformations Type: general – SubjectFull: Jacobi method Type: general – SubjectFull: T-matrix Type: general – SubjectFull: Decomposition method Type: general – SubjectFull: Matrix decomposition Type: general Titles: – TitleFull: A Unitary Transformation Extension of PolSAR Four-Component Target Decomposition. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Tingting – PersonEntity: Name: NameFull: Suo, Zhiyong – PersonEntity: Name: NameFull: Ti, Jingjing – PersonEntity: Name: NameFull: Yan, Boya – PersonEntity: Name: NameFull: Xiang, Hongli – PersonEntity: Name: NameFull: Xi, Jiabao IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 03 Text: Mar2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 16 – Type: issue Value: 6 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
