Semantic Segmentation of Remote Sensing Imagery Using Object-Based Markov Random Field Model with Regional Penalties

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 8, Issue 5, 2015, Pages 1924-1935

  Zheng, Chen ^a,b   Wang, Leiguang ^c  

^a HENAN UNIVERSITY   (China)

^b CHINESE ACADEMY OF SCIENCES   (China)

^c SOUTHWEST FORESTRY UNIVERSITY   (China)

Author keywords

Object based Markov random field (OMRF); regional penalties; remote sensing images; semantic segmentation

Indexed keywords

IMAGE RECONSTRUCTION; MARKOV PROCESSES; REMOTE SENSING; SEMANTICS;

MARKOV RANDOM FIELD MODEL; MARKOV RANDOM FIELDS; PROBABILISTIC INFERENCE; REGIONAL PENALTIES; REMOTE SENSING IMAGERY; REMOTE SENSING IMAGES; SEMANTIC SEGMENTATION; STATE-OF-THE-ART METHODS;

IMAGE SEGMENTATION;

IMAGE ANALYSIS; MARKOV CHAIN; MODELING; RANDOM WALK METHOD; REMOTE SENSING; SATELLITE IMAGERY; SEGMENTATION;

EID: 85027953873     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2014.2361756     Document Type: Article

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