Improved segmentation of a series of remote sensing images by using a fusion MRF model

Tamas Sziranyi, Maha Shadaydeh

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

2 Citations (Scopus)

Abstract

Classifying segments and detection of changes in terrestrial areas are important and time-consuming efforts for remote-sensing image repositories. Some country areas are scanned frequently (e.g. year-by-year) to spot relevant changes, and several repositories contain multi-temporal image samples for the same area in very different quality and details. We propose a Multi-Layer Markovian adaptive fusion on Luv color images and similarity measure for the segmentation and detection of changes in a series of remote sensing images. We aim the problem of detecting details in rarely scanned remote sensing areas, where trajectory analysis or direct comparison is not applicable. Our method applies unsupervised or partly supervised clustering based on a cross-image featuring, followed by multilayer MRF segmentation in the mixed dimensionality. On the base of the fused segmentation, the clusters of the single layers are trained by clusters of the mixed results. The improvement of this (partly) unsupervised method has been validated on remotely sensed image series.

Original languageEnglish
Title of host publicationProceedings - International Workshop on Content-Based Multimedia Indexing
Pages137-142
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 11th International Workshop on Content-Based Multimedia Indexing, CBMI 2013 - Veszprem, Hungary
Duration: Jun 17 2013Jun 19 2013

Other

Other2013 11th International Workshop on Content-Based Multimedia Indexing, CBMI 2013
CountryHungary
CityVeszprem
Period6/17/136/19/13

Fingerprint

Remote sensing
Fusion reactions
Multilayers
Trajectories
Color

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Information Systems

Cite this

Sziranyi, T., & Shadaydeh, M. (2013). Improved segmentation of a series of remote sensing images by using a fusion MRF model. In Proceedings - International Workshop on Content-Based Multimedia Indexing (pp. 137-142). [6576571] https://doi.org/10.1109/CBMI.2013.6576571

Improved segmentation of a series of remote sensing images by using a fusion MRF model. / Sziranyi, Tamas; Shadaydeh, Maha.

Proceedings - International Workshop on Content-Based Multimedia Indexing. 2013. p. 137-142 6576571.

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

Sziranyi, T & Shadaydeh, M 2013, Improved segmentation of a series of remote sensing images by using a fusion MRF model. in Proceedings - International Workshop on Content-Based Multimedia Indexing., 6576571, pp. 137-142, 2013 11th International Workshop on Content-Based Multimedia Indexing, CBMI 2013, Veszprem, Hungary, 6/17/13. https://doi.org/10.1109/CBMI.2013.6576571
Sziranyi T, Shadaydeh M. Improved segmentation of a series of remote sensing images by using a fusion MRF model. In Proceedings - International Workshop on Content-Based Multimedia Indexing. 2013. p. 137-142. 6576571 https://doi.org/10.1109/CBMI.2013.6576571
Sziranyi, Tamas ; Shadaydeh, Maha. / Improved segmentation of a series of remote sensing images by using a fusion MRF model. Proceedings - International Workshop on Content-Based Multimedia Indexing. 2013. pp. 137-142
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