Hyperspectral Image Stripe Detection and Correction Using Gabor Filters and Subspace Representation

Bing Zhang, Yashinov Aziz, Zhicheng Wang*, Lina ZHUANG, Kwok Po NG, Lianru Gao

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

9 Citations (Scopus)


Hyperspectral images (HSIs) exist in directional stripes commonly due to the failure of pushbroom acquisition. These stripes are not only vertically and horizontally oriented but also tend to be oblique. Furthermore, they can also be aperiodic and heavy. To address this problem, we propose a hyperspectral destriping algorithm, namely, GF-destriping. Taking advantage of the high sparsity and strong directionality of stripes in HSIs, Gabor filters are used to detect the stripes band by band first, and then, an advanced inpainting method, FastHyIn, is used to recover to the striped image. The numerical experiments on simulated data and real data sets show that our proposed algorithm is efficient and superior to state-of-the-art HSI destriping algorithms.

Original languageEnglish
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Early online date11 Mar 2021
Publication statusPublished - Jan 2022

Scopus Subject Areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering

User-Defined Keywords

  • Denoising
  • Gabor filter
  • hyperspectral image (HSI)
  • inpainting


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