Unsupervised Segmentation Of Non Stationary Images With Non Gaussian Correlated Noise Using Triplet Markov Fields And The Pearson System

Author(s):  
D. Benboudjema ◽  
W. Pieczynski
2018 ◽  
Vol 102 ◽  
pp. 41-59
Author(s):  
Lin An ◽  
Ming Li ◽  
Mohamed El Yazid Boudaren ◽  
Wojciech Pieczynski

2011 ◽  
Vol 91 (2) ◽  
pp. 163-175 ◽  
Author(s):  
Pierre Lanchantin ◽  
Jérôme Lapuyade-Lahorgue ◽  
Wojciech Pieczynski

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1913-1920 ◽  
Author(s):  
Luis Tenorio

Non‐Gaussian modeling is used to generalize Wiener—Levinson (WL) deconvolution and to obtain a procedure that is more robust to nonstationarities in the reflectivity and to correlated noise. This generalization can lead to up to a 60% reduction in the dynamic range of the residual wavelet’s amplitude response and in the rms error of phase estimates. In addition, it reduces to WL deconvolution when the reflectivity is Gaussian or when noise masks the nonstationary features of the reflectivity.


2019 ◽  
Vol 9 (4) ◽  
pp. 266-279
Author(s):  
Palahin V.V. ◽  
◽  
Ivchenko A.V. ◽  
Palahina E.A. ◽  
Viediernikov D.A. ◽  
...  

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