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Automatic ROI selection for JPEG2000 compression of remote sensing images

  • Xi'an Jiaotong University
  • IEEE

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

7 Scopus citations

Abstract

Recently, remote sensing images increase greatly in the repositories. To achieve efficient storage and indexing, we introduce a JPEG2000 compression frame which puts emphasis on selection and designation of regions of interest (ROI). Firstly, SIFT is applied for feature extraction, descriptor generation and point matching to locate ROI. Secondly, an approach is proposed for computing transformation parameters such as rotation, scale and translation separately. To get robust results, we put forward an improved RANSAC algorithm with two cost functions to obtain comparative computation efficiency in our application. At last ROI designated is used in JPEG2000 for remote sensing image compression. The method performs great in a series of experiments and satisfying results can be seen.

Original languageEnglish
Title of host publicationICSC 2007 International Conference on Semantic Computing
Pages615-621
Number of pages7
DOIs
StatePublished - 2007
EventICSC 2007 International Conference on Semantic Computing - Irvine CA, United States
Duration: 17 Sep 200719 Sep 2007

Publication series

NameICSC 2007 International Conference on Semantic Computing

Conference

ConferenceICSC 2007 International Conference on Semantic Computing
Country/TerritoryUnited States
CityIrvine CA
Period17/09/0719/09/07

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