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UID:pretalx-foss4g-asia-2023-RC7L8H@talks.osgeo.org
DTSTART;TZID=KST:20231130T170000
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DESCRIPTION:The registration of multi-modal satellite images (e.g.\, SAR\, 
 EO) is essential in fields using multiple images such as time series analy
 sis\, change detection\, and image fusion. The usability of satellite imag
 es acquired from various sensors can be increased only when the images are
  accurately registered to each other. However\, multi-modal satellite imag
 e registration is still challenging due to the different characteristics o
 f the images. Therefore\, in order to explore an effective way for multi-m
 odal satellite image registration\, this study intends to apply a matching
  method using feature extractors of pre-trained deep neural networks and c
 ompare the matching performance of the models.\n\nThis work was supported 
 by the Agency For Defense Development by the Korean Government.
DTSTAMP:20260818T233945Z
LOCATION:Gallery 3
SUMMARY:Multi-modal satellite image registration - Mi-Kyeong Kim
URL:https://talks.osgeo.org/foss4g-asia-2023/talk/RC7L8H/
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