دورية أكاديمية

A Review of Unsupervised Band Selection Techniques: Land Cover Classification for Hyperspectral Earth Observation Data

التفاصيل البيبلوغرافية
العنوان: A Review of Unsupervised Band Selection Techniques: Land Cover Classification for Hyperspectral Earth Observation Data
المؤلفون: Patro R. N., Subudhi S., Biswal P. K., Dell'Acqua F.
المساهمون: Patro, R. N., Subudhi, S., Biswal, P. K., Dell'Acqua, F.
سنة النشر: 2021
المجموعة: IRIS UNIPV (Università degli studi di Pavia)
الوصف: A hyperspectral image (HSI) is a collection of several narrow-band images that span a wide spectral range. Each band reflects the same scene, composed of various objects imaged at different wavelengths; the spatial information, however, remains generally consistent across bands. Both types of information, spectral and spatial, can be leveraged to identify and classify objects. Recently, the use of machine learning (ML) in object classification has become increasingly widespread. Regardless of the selected approach, object-specific spectral and spatial information is key to discriminating relevant categories. Whereas spatial information is usually repeated across bands, spectral information tends to be distributed more unevenly and often highly so. This poses the issue of removing redundancy, which is commonly called the band selection (BS) problem and refers to identifying an optimal subset of bands for further HSI processing.
نوع الوثيقة: article in journal/newspaper
وصف الملف: ELETTRONICO
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:000701246700013; volume:9; issue:3; firstpage:72; lastpage:111; numberofpages:40; journal:IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE; http://hdl.handle.net/11571/1443754Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85101771131; https://ieeexplore.ieee.org/document/9361697Test
DOI: 10.1109/MGRS.2021.3051979
الإتاحة: https://doi.org/10.1109/MGRS.2021.3051979Test
http://hdl.handle.net/11571/1443754Test
https://ieeexplore.ieee.org/document/9361697Test
رقم الانضمام: edsbas.BA2227C8
قاعدة البيانات: BASE