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Hyperspectral Image Spectral–Spatial-Range Gabor Filtering

Lin He,Chenying Liu,Jun Li,Yuanqing Li,Shutao Li,Zhuliang Yu

Published 2020 in IEEE Transactions on Geoscience and Remote Sensing

ABSTRACT

Spectral–spatial Gabor filtering, which is based on 3-D local harmonic analysis, has been a powerful spectral–spatial feature extraction tool for hyperspectral image (HSI) classification. However, existing spectral–spatial Gabor approaches are prone to oversmoothing, neglecting the existences of edges and negatively affecting the classification. In this article, we propose a new HSI Gabor filtering concept, called spectral–spatial-range Gabor filtering, which intends to restrain edge interference from disturbing local spectral–spatial harmonic components. Contributions and novelties of our work can be identified as follows: 1) an HSI filtering framework is created, which can accommodate various Gabor filtering procedures and hence offer the potential to guide the design of new Gabor filters; 2) following such a unified filtering framework and taking into consideration both local spectral–spatial harmonic characteristics and range domain variations, we develop a new concept of spectral–spatial-range Gabor filtering; and 3) utilizing this proposed Gabor prototype and elaborating mathematical derivations, we achieve a novel discriminative spectral–spatial-range Gabor filtering method, which can deal with discriminative local harmonics and edge interference simultaneously along the spectral–spatial-range domain, obtaining highly discriminative Gabor features while yielding linear computational complexity. Our novel method is evaluated on four real HSI data sets and achieves excellent performances.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    IEEE Transactions on Geoscience and Remote Sensing

  • Publication date

    2020-02-05

  • Fields of study

    Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1109/TGRS.2020.2967778
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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