Sparse coding based airport detection from medium resolution Landsat-7 satellite remote sensing images

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A simple but effective method for airport detection from medium resolution Landsat-7 satellite remote sensing images based on sparse coding is presented. It consists of three phases: dictionary construction, sparse coding, and airport detection. Firstly, an over-complete dictionary is constructed using a set of airport training samples. Secondly, test images are scanned using multi-scale windows and each scanned window is sparsely coded in terms of atoms of the dictionary. Finally, sparsity concentration index of each scanned window is calculated based on the coding coefficients, which is used to decide the airport detection. Evaluations on publically available satellite images and comparisons with state-of-the-art approaches have demonstrated the superiority of the presented work.

Original languageEnglish
Title of host publication3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 - Proceedings
EditorsQihao Weng, Paolo Gamba, George Xian, Guangxing Wang, Guangxing Wang, Jianjun Zhu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages226-230
Number of pages5
ISBN (Electronic)9781479941841
DOIs
StatePublished - 16 Oct 2014
Event3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 - Changsha, China
Duration: 11 Jun 201414 Jun 2014

Publication series

Name3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014 - Proceedings

Conference

Conference3rd International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2014
Country/TerritoryChina
CityChangsha
Period11/06/1414/06/14

Keywords

  • airport detection
  • Landsat-7 satellite images
  • multi-scale
  • sparse coding

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