WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653

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Publisher: search.filters.publisher.Springer London LtdSubject: search.filters.subject.Anomaly Detection

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  • Article
    Citation - WoS: 8
    Citation - Scopus: 10
    Sparse Coding of Hyperspectral Imagery Using Online Learning
    (Springer London Ltd, 2015) Toreyin, Behcet Ugur; Ulku, Irem
    Sparse coding ensures to express the data in terms of a few nonzero dictionary elements. Since the data size is large for hyperspectral imagery, it is reasonable to use sparse coding for compression of hyperspectral images. In this paper, a hyperspectral image compression method is proposed using a discriminative online learning-based sparse coding algorithm. Compression and anomaly detection tests are performed on hyperspectral images from the AVIRIS dataset. Comparative rate-distortion analyses indicate that the proposed method is superior to the state-of-the-art hyperspectral compression techniques.