A Markov Random Field Approach for Topology-Preserving Registration: Application to Object-Based Tomographic Image Interpolation

Reconstruction for distributed video coding: a Markov random field approach with context-adaptive smoothness prior

10.1117/12.863504 ◽

2010 ◽

Cited By ~ 1

Author(s):

Yongsheng Zhang ◽

Hongkai Xiong ◽

Zhihai He ◽

Songyu Yu

Keyword(s):

Video Coding ◽

Random Field ◽

Markov Random Field ◽

Distributed Video Coding ◽

Field Approach ◽

A Finite Markov Random Field approach to fast edge-preserving image recovery

Image and Vision Computing ◽

10.1016/j.imavis.2006.05.021 ◽

2007 ◽

Vol 25 (6) ◽

pp. 792-804 ◽

Cited By ~ 11

Author(s):

Michele Ceccarelli

Keyword(s):

Random Field ◽

Markov Random Field ◽

Image Recovery ◽

Edge Preserving ◽

Field Approach ◽

Interactive Image Segmentation using Improved Adaptive Markov Random Field Approach

Indian Journal of Science and Technology ◽

10.17485/ijst/2017/v10i6/94636 ◽

2017 ◽

Vol 10 (6) ◽

pp. 1-9

Author(s):

G. S. Gowri ◽

P. Ponmuthuramalingam ◽

◽

Keyword(s):

Image Segmentation ◽

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Interactive Image Segmentation ◽

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 ◽

Computer Aided Systems Theory - EUROCAST 2003 - Lecture Notes in Computer Science ◽

A Novel Gauss-Markov Random Field Approach for Regularization of Diffusion Tensor Maps

10.1007/978-3-540-45210-2_46 ◽

2003 ◽

pp. 506-517 ◽

Cited By ~ 9

Author(s):

Marcos Martín-Fernández ◽

Raul San Josá-Estépar ◽

Carl-Fredrik Westin ◽

Carlos Alberola-López

Keyword(s):

Random Field ◽

Markov Random Field ◽

Diffusion Tensor ◽

Field Approach ◽

Power Line Extraction From Aerial Images Using Object-Based Markov Random Field With Anisotropic Weighted Penalty

IEEE Access ◽

10.1109/access.2019.2939025 ◽

2019 ◽

Vol 7 ◽

pp. 125333-125356 ◽

Cited By ~ 3

Author(s):

Le Zhao ◽

Xianpei Wang ◽

Hongtai Yao ◽

Meng Tian ◽

Zini Jian

Keyword(s):

Random Field ◽

Markov Random Field ◽

Power Line ◽

Aerial Images ◽

Line Extraction ◽

Markov Random ◽

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258) ◽

Object-based image segmentation using DWT/RDWT multiresolution Markov random field

10.1109/icassp.1999.757593 ◽

1999 ◽

Cited By ~ 3

Author(s):

Lei Zheng ◽

J.C. Liu ◽

A.K. Chan ◽

W. Smith

Keyword(s):

Image Segmentation ◽

Random Field ◽

Markov Random Field ◽

Markov Random ◽

A Markov Random Field Approach to Edge Detection

MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference ◽

10.1109/melcon.2006.1653143 ◽

2006 ◽

Cited By ~ 2

Author(s):

L.J. Tardon ◽

I. Barbancho ◽

F. Marquez

Keyword(s):

Edge Detection ◽

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. ◽

A Markov random field approach to microarray image gridding

10.1109/icpr.2004.1334588 ◽

2004 ◽

Cited By ~ 16

Author(s):

G. Antoniol ◽

M. Ceccarelli

Keyword(s):

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Microarray Image ◽

Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

IEEE Transactions on Image Processing ◽

10.1109/tip.2016.2622401 ◽

2017 ◽

Vol 26 (1) ◽

pp. 426-438 ◽

Cited By ~ 11

Author(s):

Peng Chen ◽

James D. B. Nelson ◽

Jean-Yves Tourneret

Keyword(s):

Random Field ◽

Markov Random Field ◽

Field Approach ◽

Hyperspectral Unmixing ◽