A new methodology for spectral-spatial classification of hyperspectral images

Zelang Miao, Wen Zhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Recent developments in hyperspectral images have heightened the need for advanced classification methods. To reach this goal, this paper proposed an improved spectral-spatial method for hyperspectral image classification. The proposed method mainly consists of three steps. First, four band selection strategies are proposed to utilize the statistical region merging (SRM) method to segment the hyperspectral image. The segmentation map is subsequently integrated with the pixel-wise classification method to classify the hyperspectral image. Finally, the final classification result is obtained using the decision fusion rule. Validation tests are performed to evaluate the performance of the proposed approach, and the results indicate that the new proposed approach outperforms the state-of-the-art methods.
Original languageEnglish
Article number1538973
JournalJournal of Sensors
Volume2016
DOIs
Publication statusPublished - 1 Jan 2016

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Instrumentation
  • Electrical and Electronic Engineering

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