Gibbs random field model based weight selection for the 2-D adaptive weighted median filter

L. Onural; M. Bilge Alp; M. Izzet Gurelli

doi:10.1109/34.308480

Gibbs random field model based weight selection for the 2-D adaptive weighted median filter

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/34.308480 ◽

1994 ◽

Vol 16 (8) ◽

pp. 831-837 ◽

Cited By ~ 5

Author(s):

L. Onural ◽

M. Bilge Alp ◽

M. Izzet Gurelli

Keyword(s):

Random Field ◽

Field Model ◽

Median Filter ◽

Gibbs Random Field ◽

Random Field Model ◽

Model Based ◽

Weighted Median ◽

Selection For ◽

Weighted Median Filter

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Weight selection for the 2-d adaptive weighted median filter based on the gibbs random field model

IEEE Winter Workshop on Nonlinear Digital Signal Processing ◽

10.1109/ndsp.1993.767720 ◽

2005 ◽

Author(s):

L. Onural ◽

M.B. Alp

Keyword(s):

Random Field ◽

Field Model ◽

Median Filter ◽

Gibbs Random Field ◽

Random Field Model ◽

Weighted Median ◽

Selection For ◽

Weighted Median Filter

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Gibbs random field model based 3D motion estimation from video sequences

10.1117/12.186006 ◽

1994 ◽

Author(s):

A. A. Alatan ◽

Levent Onural

Keyword(s):

Motion Estimation ◽

Random Field ◽

Field Model ◽

Video Sequences ◽

Gibbs Random Field ◽

Random Field Model ◽

3D Motion ◽

Model Based ◽

3D Motion Estimation

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Gibbs random field model based 3-D motion estimation by weakened rigidity

Proceedings of 1st International Conference on Image Processing ◽

10.1109/icip.1994.413679 ◽

2002 ◽

Cited By ~ 4

Author(s):

A.A. Alatan ◽

L. Onural

Keyword(s):

Motion Estimation ◽

Random Field ◽

Field Model ◽

Gibbs Random Field ◽

Random Field Model ◽

Model Based

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Semantic Segmentation of PolSAR Images Using Conditional Random Field Model Based on Deep Features

Journal of Physics Conference Series ◽

10.1088/1742-6596/1168/4/042008 ◽

2019 ◽

Vol 1168 ◽

pp. 042008

Author(s):

Tao Hu ◽

Wei-hua Li ◽

Xian-xiang Qin

Keyword(s):

Random Field ◽

Field Model ◽

Conditional Random Field ◽

Semantic Segmentation ◽

Random Field Model ◽

Model Based ◽

Conditional Random Field Model

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Composite Kernel and Hybrid Discriminative Random Field Model Based on Feature Fusion for PolSAR Image Classification

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2020.2990711 ◽

2020 ◽

pp. 1-5

Author(s):

Wanying Song ◽

Yan Wu ◽

Ping Guo

Keyword(s):

Random Field ◽

Image Classification ◽

Field Model ◽

Feature Fusion ◽

Random Field Model ◽

Model Based ◽

Composite Kernel

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Image interpolation using a simple Gibbs random field model

Proceedings., International Conference on Image Processing ◽

10.1109/icip.1995.529754 ◽

2002 ◽

Cited By ~ 1

Author(s):

N. Herodotou ◽

A.N. Venetsanopoulos ◽

L. Onural

Keyword(s):

Random Field ◽

Field Model ◽

Image Interpolation ◽

Gibbs Random Field ◽

Random Field Model

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Segmentation of images for environmental studies using a simple Markov/Gibbs random field model

Computer Analysis of Images and Patterns - Lecture Notes in Computer Science ◽

10.1007/3-540-60268-2_280 ◽

1995 ◽

pp. 57-64

Author(s):

Georgy Gimel'farb ◽

Nelly Kovalevskaya

Keyword(s):

Random Field ◽

Field Model ◽

Environmental Studies ◽

Gibbs Random Field ◽

Random Field Model ◽

Segmentation Of Images

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A random-field model-based algorithm for anomalous complex image pixel detection

IEEE Transactions on Image Processing ◽

10.1109/83.136595 ◽

1992 ◽

Vol 1 (2) ◽

pp. 186-196 ◽

Cited By ~ 5

Author(s):

M.G. Bello

Keyword(s):

Random Field ◽

Field Model ◽

Random Field Model ◽

Model Based ◽

Complex Image

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Markov-Gibbs Random Field Model for Improved Full-Cardiac Cycle Strain Estimation from Tagged CMR

Journal of Cardiovascular Magnetic Resonance ◽

10.1186/1532-429x-14-s1-p258 ◽

2012 ◽

Vol 14 (S1) ◽

Author(s):

Matthew J Nitzken ◽

Ayman S El-Baz ◽

Garth M Beache

Keyword(s):

Random Field ◽

Cardiac Cycle ◽

Field Model ◽

Gibbs Random Field ◽

Random Field Model ◽

Strain Estimation

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A Two-Stage Conditional Random Field Model Based Framework for Multi-Label Classification

Lecture Notes in Computer Science - Pattern Recognition and Machine Intelligence ◽

10.1007/978-3-319-69900-4_9 ◽

2017 ◽

pp. 69-76

Author(s):

Abhiram Kumar Singh ◽

C. Chandra Sekhar

Keyword(s):

Random Field ◽

Field Model ◽

Conditional Random Field ◽

Two Stage ◽

Random Field Model ◽

Model Based ◽

Conditional Random Field Model

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