Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods

Ufuk Kaya; Behcet Ugur Toreyin; Fatma Kucuk

doi:10.1109/MIGARS67156.2025.11232406

Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods

Ufuk Kaya^*
, Behcet Ugur Toreyin
, Fatma Kucuk

^*Bu çalışma için yazışmadan sorumlu yazar

Bilişim Enstitüsü

Istanbul Technical University
Yildirim Beyazit Universitesi

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

This paper proposes a hybrid anomaly detection framework for hyperspectral images by combining Robust Sub-space Recovery (RoSuRe) and Local Anomaly Detection (LAD). Both RoSuRe and its variant Fixed Dictionary RoSuRe (FD-RoSuRe) are evaluated with LAD-C and LAD-C-S across multiple datasets. Experiments with heatmaps, ROC curves, and AUC scores show that FD-RoSuRe with LAD-C-S yields the most accurate and localized detection, especially in structured and cluttered environments.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798331579203
DOI'lar	https://doi.org/10.1109/MIGARS67156.2025.11232406
Yayın durumu	Yayınlandı - 2025
Etkinlik	3rd International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025 - Bucharest, Romania Süre: 2 Eyl 2025 → 4 Eyl 2025

Yayın serisi

Adı	2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	3rd International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025
Ülke/Bölge	Romania
Şehir	Bucharest
Periyot	2/09/25 → 4/09/25

Bibliyografik not

Publisher Copyright:
© 2025 IEEE.

Belgeye Erişim

10.1109/MIGARS67156.2025.11232406

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kaya, U., Toreyin, B. U., & Kucuk, F. (2025). Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods. In 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025 (2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MIGARS67156.2025.11232406

Kaya, Ufuk ; Toreyin, Behcet Ugur ; Kucuk, Fatma. / Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods. 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025).

@inproceedings{36874ee0a27246da9fabe8d38121a33a,

title = "Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods",

abstract = "This paper proposes a hybrid anomaly detection framework for hyperspectral images by combining Robust Sub-space Recovery (RoSuRe) and Local Anomaly Detection (LAD). Both RoSuRe and its variant Fixed Dictionary RoSuRe (FD-RoSuRe) are evaluated with LAD-C and LAD-C-S across multiple datasets. Experiments with heatmaps, ROC curves, and AUC scores show that FD-RoSuRe with LAD-C-S yields the most accurate and localized detection, especially in structured and cluttered environments.",

author = "Ufuk Kaya and Toreyin, \{Behcet Ugur\} and Fatma Kucuk",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 3rd International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025 ; Conference date: 02-09-2025 Through 04-09-2025",

year = "2025",

doi = "10.1109/MIGARS67156.2025.11232406",

language = "English",

series = "2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025",

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

booktitle = "2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025",

address = "United States",

}

Kaya, U, Toreyin, BU & Kucuk, F 2025, Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods. in 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025. 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025, Institute of Electrical and Electronics Engineers Inc., 3rd International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025, Bucharest, Romania, 2/09/25. https://doi.org/10.1109/MIGARS67156.2025.11232406

Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods. / Kaya, Ufuk; Toreyin, Behcet Ugur; Kucuk, Fatma.
2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods

AU - Kaya, Ufuk

AU - Toreyin, Behcet Ugur

AU - Kucuk, Fatma

PY - 2025

Y1 - 2025

N2 - This paper proposes a hybrid anomaly detection framework for hyperspectral images by combining Robust Sub-space Recovery (RoSuRe) and Local Anomaly Detection (LAD). Both RoSuRe and its variant Fixed Dictionary RoSuRe (FD-RoSuRe) are evaluated with LAD-C and LAD-C-S across multiple datasets. Experiments with heatmaps, ROC curves, and AUC scores show that FD-RoSuRe with LAD-C-S yields the most accurate and localized detection, especially in structured and cluttered environments.

AB - This paper proposes a hybrid anomaly detection framework for hyperspectral images by combining Robust Sub-space Recovery (RoSuRe) and Local Anomaly Detection (LAD). Both RoSuRe and its variant Fixed Dictionary RoSuRe (FD-RoSuRe) are evaluated with LAD-C and LAD-C-S across multiple datasets. Experiments with heatmaps, ROC curves, and AUC scores show that FD-RoSuRe with LAD-C-S yields the most accurate and localized detection, especially in structured and cluttered environments.

UR - https://www.scopus.com/pages/publications/105025423505

U2 - 10.1109/MIGARS67156.2025.11232406

DO - 10.1109/MIGARS67156.2025.11232406

M3 - Conference contribution

AN - SCOPUS:105025423505

T3 - 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025

BT - 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025

Y2 - 2 September 2025 through 4 September 2025

ER -

Kaya U, Toreyin BU, Kucuk F. Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods. In 2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (2025 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2025). doi: 10.1109/MIGARS67156.2025.11232406

Hybrid Hyperspectral Anomaly Detection via Robust Subspace Recovery and Laplacian Cauchy-Based Methods

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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