An eigenvalue-based approach for structure classification in polarimetric SAR images

Biondi, Filippo and Clemente, Carmine and Orlando, Danilo (2019) An eigenvalue-based approach for structure classification in polarimetric SAR images. IEEE Geoscience and Remote Sensing Letters. pp. 1-5. ISSN 1545-598X (In Press)

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    Abstract

    In this paper, we design a novel unsupervised architecture for automatic classification of the dominant polarization in polarimetric SAR images. To this end, we leverage the ideas developed in [1] and suitably exploit them to build a decision logic capable of recognizing the dominant scattering mechanism which characterizes the pixel under test. Specifically, we combine the original data to generate three different sets of reduced-size vectors, which feed a dominant eigenvalues classifier based upon the Model Order Selection rules. Then, the outputs of the latter classification schemes are exploited to infer, according to a specific criterion, the dominant polarization. The performance analysis is conducted on measured data and points out the effectiveness of the newly proposed classification architecture also showing that information about the dominant polarization canbe representative of the type of structure which gives raise to the dominant backscattering mechanism.

    Author(s):Biondi, Filippo, Clemente, Carmine ORCID logoORCID: https://orcid.org/0000-0002-6665-693X and Orlando, Danilo
    Item type:Article
    ID code:69732
    Notes:© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Keywords:covariance matrix, eigenvalues decomposition, model order selection rules, polarimetric SAR image classification, structure classification, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Strategic Research Themes > Ocean, Air and Space
    Strategic Research Themes > Measurement Science and Enabling Technologies
    Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:10 Sep 2019 13:47
    Last modified:18 Nov 2019 03:28
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/69732
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