Multimodal Change Detection in Remote Sensing Images Using an Unsupervised Pixel Pairwise Based Markov Random Field Model

IEEE Transactions on Image Processing ◽

10.1109/tip.2019.2933747 ◽

2019 ◽

pp. 1-1 ◽

Cited By ~ 6

Author(s):

Redha Touati ◽

Max Mignotte ◽

Mohamed Dahmane

Keyword(s):

Remote Sensing ◽

Change Detection ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Remote Sensing Images ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random

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Multigranularity Multiclass-Layer Markov Random Field Model for Semantic Segmentation of Remote Sensing Images

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2020.3033293 ◽

2020 ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Chen Zheng ◽

Yun Zhang ◽

Leiguang Wang

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Semantic Segmentation ◽

Remote Sensing Images ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random

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Semantic Segmentation of Remote Sensing Imagery Using an Object-Based Markov Random Field Model With Auxiliary Label Fields

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2017.2658731 ◽

2017 ◽

Vol 55 (5) ◽

pp. 3015-3028 ◽

Cited By ~ 14

Author(s):

Chen Zheng ◽

Yun Zhang ◽

Leiguang Wang

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Semantic Segmentation ◽

Random Field Model ◽

Remote Sensing Imagery ◽

Markov Random Field Model ◽

Markov Random ◽

Object Based

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An Advanced Superpixel-Based Markov Random Field Model for Unsupervised Change Detection

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2019.2948660 ◽

2020 ◽

Vol 17 (8) ◽

pp. 1401-1405 ◽

Cited By ~ 2

Author(s):

Ming Hao ◽

Mengchao Zhou ◽

Jian Jin ◽

Wenzhong Shi

Keyword(s):

Change Detection ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random

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A Hybrid Markov Random Field Model With Multi-Granularity Information for Semantic Segmentation of Remote Sensing Imagery

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

10.1109/jstars.2019.2917128 ◽

2019 ◽

Vol 12 (8) ◽

pp. 2728-2740 ◽

Cited By ~ 1

Author(s):

Chen Zheng ◽

Leiguang Wang ◽

Xiaohui Chen

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Semantic Segmentation ◽

Random Field Model ◽

Remote Sensing Imagery ◽

Markov Random Field Model ◽

Markov Random

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Unsupervised change detection of multispectral images based on spatial constraint chi-squared transform and Markov random field model

Journal of Applied Remote Sensing ◽

10.1117/1.jrs.10.046028 ◽

2016 ◽

Vol 10 (4) ◽

pp. 046028 ◽

Cited By ~ 3

Author(s):

Aiye Shi ◽

Chao Wang ◽

Shaohong Shen ◽

Fengchen Huang ◽

Zhenli Ma

Keyword(s):

Change Detection ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Multispectral Images ◽

Spatial Constraint ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random ◽

Chi Squared

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Advanced Markov random field model based on local uncertainty for unsupervised change detection

Remote Sensing Letters ◽

10.1080/2150704x.2015.1054045 ◽

2015 ◽

Vol 6 (9) ◽

pp. 667-676 ◽

Cited By ~ 8

Author(s):

Pengfei He ◽

Wenzhong Shi ◽

Zelang Miao ◽

Hua Zhang ◽

Liping Cai

Keyword(s):

Change Detection ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Random Field Model ◽

Markov Random Field Model ◽

Model Based ◽

Markov Random ◽

Local Uncertainty

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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 ◽

10.1109/jstars.2014.2361756 ◽

2015 ◽

Vol 8 (5) ◽

pp. 1924-1935 ◽

Cited By ~ 27

Author(s):

Chen Zheng ◽

Leiguang Wang

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Semantic Segmentation ◽

Random Field Model ◽

Remote Sensing Imagery ◽

Markov Random Field Model ◽

Markov Random ◽

Object Based

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Multilayer semantic segmentation of remote-sensing imagery using a hybrid object-based Markov random field model

International Journal of Remote Sensing ◽

10.1080/01431161.2016.1244364 ◽

2016 ◽

Vol 37 (23) ◽

pp. 5505-5532

Author(s):

Chen Zheng ◽

Yun Zhang ◽

Leiguang Wang

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Semantic Segmentation ◽

Random Field Model ◽

Remote Sensing Imagery ◽

Markov Random Field Model ◽

Markov Random ◽

Object Based

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Supervised segmentation of remote-sensing multitemporal images based on the tree-structured Markov random field model

IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 ◽

10.1109/igarss.2004.1370614 ◽

2004 ◽

Cited By ~ 2

Author(s):

Giovanni Poggi Luca Cicala

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Random Field Model ◽

Markov Random Field Model ◽

Markov Random ◽

Supervised Segmentation

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Segmentation for remote-sensing imagery using the object-based Gaussian-Markov random field model with region coefficients

International Journal of Remote Sensing ◽

10.1080/01431161.2018.1563841 ◽

2019 ◽

Vol 40 (11) ◽

pp. 4441-4472 ◽

Cited By ~ 2

Author(s):

Chen Zheng ◽

Hongtai Yao

Keyword(s):

Remote Sensing ◽

Random Field ◽

Markov Random Field ◽

Field Model ◽

Random Field Model ◽

Remote Sensing Imagery ◽

Markov Random Field Model ◽

Gaussian Markov Random Field ◽

Markov Random ◽

Object Based

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