Robust change detection in high resolution satellite images with geometric distortions

Dongkwon Jin, Kyungsun Lim, Chang Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A robust change detection algorithm for high resolution satellite images, which are not perfectly registered, is proposed in this work. To achieve this goal, a change detection technique for registered images and an image registration technique are employed in a cooperative way. Specifically, we use not only hand-crafted features but also change detection results to match keypoints extracted from two images. We then align the images using the matching pairs of keypoints. Finally, we obtain a change map from the aligned images. These steps of image registration and change detection are alternately iterated until the convergence. Experimental results demonstrate that proposed algorithm outperforms the conventional change detection technique significantly, when there are geometric distortions between temporal satellite images.

Original languageEnglish
Title of host publication2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages572-577
Number of pages6
ISBN (Electronic)9781728132488
DOIs
Publication statusPublished - 2019 Nov
Event2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China
Duration: 2019 Nov 182019 Nov 21

Publication series

Name2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019

Conference

Conference2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
CountryChina
CityLanzhou
Period19/11/1819/11/21

ASJC Scopus subject areas

  • Information Systems

Fingerprint Dive into the research topics of 'Robust change detection in high resolution satellite images with geometric distortions'. Together they form a unique fingerprint.

Cite this