Unsupervised feature learning for scene classification of high resolution remote sensing image

Min Fu, Yuan Yuan, Xiaoqiang Lu

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

7 Scopus citations

Abstract

Due to the rapid development of various satellite sensors, a large amount of high resolution remote sensing images can be obtained. In order to efficiently represent the scenes from these high resolution images, an unsupervised feature learning method is proposed for high resolution image scene classification. In the proposed method, a set of filter banks are learned in an unsupervised manner from the unlabeled image patches, which are robust, efficient and do not need elaborately designed descriptors such as SIFT. And then, each image is encoded by these filter banks using a soft distance assignment scheme, generating a final feature vector to excellently represent the image scene. Finally, by virtue of the traditional SVM classifier, the sematic concepts of different scenes can be categorized. Experimental evaluation on the the high resolution remote sensing images demonstrates the effectiveness and good performance of the proposed method.

Original languageEnglish
Title of host publication2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages206-210
Number of pages5
ISBN (Electronic)9781479919482
DOIs
StatePublished - 31 Aug 2015
Externally publishedYes
EventIEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Chengdu, China
Duration: 12 Jul 201515 Jul 2015

Publication series

Name2015 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015 - Proceedings

Conference

ConferenceIEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2015
Country/TerritoryChina
CityChengdu
Period12/07/1515/07/15

Keywords

  • high resolution image
  • scene classification
  • unsupervised feature learning

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