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Signal, Image and Video Processing

, Volume 10, Issue 4, pp 745–752 | Cite as

Land-use scene classification using multi-scale completed local binary patterns

  • Chen Chen
  • Baochang Zhang
  • Hongjun Su
  • Wei Li
  • Lu Wang
Original Paper

Abstract

In this paper, we introduce the completed local binary patterns (CLBP) operator for the first time on remote sensing land-use scene classification. To further improve the representation power of CLBP, we propose a multi-scale CLBP (MS-CLBP) descriptor to characterize the dominant texture features in multiple resolutions. Two different kinds of implementations of MS-CLBP equipped with the kernel-based extreme learning machine are investigated and compared in terms of classification accuracy and computational complexity. The proposed approach is extensively tested on the 21-class land-use dataset and the 19-class satellite scene dataset showing a consistent increase on performance when compared to the state of the arts.

Keywords

Land-use scene classification Multi-scale analysis  Local binary patterns Extreme learning machine 

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Department of Electrical EngineeringUniversity of Texas at DallasRichardsonUSA
  2. 2.School of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina
  3. 3.School of Earth Science and EngineeringHohai UniversityNanjingChina
  4. 4.College of Information Science and TechnologyBeijing University of Chemical TechnologyBeijingChina

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