Extraction of building roof contours from the integration of high-resolution aerial imagery and laser data using Markov random fields

Semantic segmentation for high-resolution aerial imagery using multi-skip network and Markov random fields

2017 IEEE International Conference on Unmanned Systems (ICUS) ◽

10.1109/icus.2017.8278309 ◽

2017 ◽

Author(s):

Jiankun Li ◽

Wenrui Ding ◽

Hongguang Li ◽

Chunlei Liu

Keyword(s):

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Semantic Segmentation ◽

Aerial Imagery ◽

A novel segmentation method of high resolution remote sensing image based on object-oriented Markov random fields model

10.1117/12.912791 ◽

2011 ◽

Author(s):

Liang Hong ◽

Xianchun Pan ◽

Zhaozhong Gao ◽

Kun Yang

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Object Oriented ◽

Remote Sensing Image ◽

Segmentation Method ◽

Unsupervised change detection with high-resolution SAR images by edge-preserving Markov random fields and graph-cuts

2012 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2012.6351112 ◽

2012 ◽

Cited By ~ 3

Author(s):

Gabriele Moser ◽

Sebastiano B. Serpico

Keyword(s):

High Resolution ◽

Change Detection ◽

Random Fields ◽

Markov Random Fields ◽

Graph Cuts ◽

Sar Images ◽

Edge Preserving ◽

Classification of very high resolution SAR images of urban areas by dictionary-based mixture models, copulas, and Markov random fields using textural features

10.1117/12.865023 ◽

2010 ◽

Author(s):

Aurélie Voisin ◽

Gabriele Moser ◽

Vladimir A. Krylov ◽

Sebastiano B. Serpico ◽

Josiane Zerubia

Keyword(s):

High Resolution ◽

Mixture Models ◽

Random Fields ◽

Urban Areas ◽

Markov Random Fields ◽

Textural Features ◽

Sar Images ◽

Markov Random ◽

Very High

Change Detection Using High Resolution Remote Sensing Images Based on Active Learning and Markov Random Fields

Remote Sensing ◽

10.3390/rs9121233 ◽

2017 ◽

Vol 9 (12) ◽

pp. 1233 ◽

Cited By ~ 12

Author(s):

Huai Yu ◽

Wen Yang ◽

Guang Hua ◽

Hui Ru ◽

Pingping Huang

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Active Learning ◽

Change Detection ◽

Random Fields ◽

Markov Random Fields ◽

Remote Sensing Images ◽

Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services ◽

Segmentation of high resolution remote sensing image based on hierarchically multiscale object-oriented Markov random fields model

10.1109/icsdm.2011.5969060 ◽

2011 ◽

Author(s):

Liang Hong ◽

Zhaozhong Gao ◽

Xianchun Pan ◽

Kun Yang

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Object Oriented ◽

Remote Sensing Image ◽

Multitemporal region-based classification of high-resolution images by Markov random fields and multiscale segmentation

2011 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2011.6048908 ◽

2011 ◽

Cited By ~ 5

Author(s):

Gabriele Moser ◽

Sebastiano B. Serpico

Keyword(s):

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Markov Random ◽

Multiscale Segmentation ◽

High Resolution Images

Unsupervised change detection with very high-resolution SAR images by multiscale analysis and Markov random fields

2010 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2010.5652435 ◽

2010 ◽

Cited By ~ 3

Author(s):

Gabriele Moser ◽

Sebastiano B. Serpico

Keyword(s):

High Resolution ◽

Change Detection ◽

Random Fields ◽

Multiscale Analysis ◽

Markov Random Fields ◽

Sar Images ◽

Markov Random ◽

Very High

Use of Markov Random Fields for automatic cloud/shadow detection on high resolution optical images

ISPRS Journal of Photogrammetry and Remote Sensing ◽

10.1016/j.isprsjprs.2008.12.007 ◽

2009 ◽

Vol 64 (4) ◽

pp. 351-366 ◽

Cited By ~ 54

Author(s):

Sylvie Le Hégarat-Mascle ◽

Cyrille André

Keyword(s):

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Shadow Detection ◽

Markov Random ◽

Optical Images

2011 International Conference on Remote Sensing, Environment and Transportation Engineering ◽

A novel segmentation method of high resolution remote sensing image based on multi-feature object-oriented Markov random fields model

10.1109/rsete.2011.5964014 ◽

2011 ◽

Author(s):

Liang Hong ◽

Kun Yang

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Random Fields ◽

Markov Random Fields ◽

Object Oriented ◽

Remote Sensing Image ◽

Segmentation Method ◽