Fuzzy Super Resolution Mapping Based on Markov Random Fields

Author

Tolpekin, V.A. ; Hamm, N.A.S.

Author_Institution

Dept. of Earth Obs. Sci., Int. Inst. for Geo-Inf. Sci. & Earth Obs., Enschede

Volume

2

fYear

2008

fDate

7-11 July 2008

Abstract

Recent research has used Markov Random Fields (MRF) as a method for super-resolution mapping (SRM). This paper investigated the per-pixel uncertainty associated with MRF based SRM. This provided insight into the spatial distribution of uncertainty associated with SRM. Furthermore, the map of per-pixel uncertainty clearly shows the boundary between land-cover classes and this may provide an input for image segmentation. The insight provided by the per-pixel uncertainty together with the class boundaries will be valuable for development of the MRF approach to super-resolution mapping.

Keywords

Markov processes; fuzzy logic; geophysics computing; image classification; image segmentation; terrain mapping; MRF based SRM; Markov random fields; fuzzy super-resolution mapping; image segmentation; per-pixel uncertainty spatial distribution; Genetic algorithms; Geoscience; Hopfield neural networks; Image classification; Image resolution; Image segmentation; Markov random fields; Pixel; Spatial resolution; Uncertainty; Image classification; Markov Random Fields; superresolution mapping; uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4779134

Filename

4779134