A 3-D Gabor Phase-Based Coding and Matching Framework for Hyperspectral Imagery Classification

Sen Jia, Linlin Shen, Jiasong Zhu, Qingquan Li

Research output: Journal PublicationArticlepeer-review

58 Citations (Scopus)

Abstract

As manual labeling is very difficult and time-consuming, the labeled samples used to train a supervised classifier are generally limited, which become one of the biggest challenge for hyperspectral imagery classification. In order to tackle this issue, a recent trend is to exploit the structure information of materials, as which reflects the region homogeneity in the spatial domain and offers an invaluable complement to the spectral information. In this respect, 3-D Gabor wavelets have been introduced to extract joint spectral-spatial features for hyperspectral images. One the one hand, the features extracted by 3-D Gabor wavelets lead to very good performance for classification. On the other hand, its drawbacks, i.e., big number of features and high computational cost, limit its applicability. In this paper, a 3-D Gabor-wavelet-based phase coding and Hamming distance-based matching (3DGPC-HDM) framework is developed for hyperspectral imagery classification. The proposed method, instead of taking into account the large volume of Gabor magnitude features, exploits the Gabor phase features with certain orientations (i.e., the direction parallel to the spectral axis), which are then encoded by a simple quadrant bit coding scheme. After that, a normalized Hamming distance matching (HDM) method is adopted to determine the similarity of two samples, and the nearest neighbor classifier is routinely utilized for pixelwise recognition. Finally, experiments on three real hyperspectral data sets show that the proposed 3DGPC-HDM leads to very good performance. Comparisons with the state-of-the-art methods in the literature, in terms of both classifier complexity and generalization ability from very small training sets, are also included.

Original languageEnglish
Pages (from-to)1176-1188
Number of pages13
JournalIEEE Transactions on Cybernetics
Volume48
Issue number4
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Keywords

  • Gabor wavelets
  • hyperspectral imagery classification
  • phase coding

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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