Classification via Hidden Markov Trees for a Vision-Based Approach to Conveying Webpages to Users with Assistive Needs

2016 ◽  
Author(s):  
Michael Cormier ◽  
Richard Mann ◽  
Robin Cohen ◽  
Kary Moffatt
Keyword(s):  
Hidden Markov ◽  
Hidden Markov Trees

Multiscale texture segmentation of dip‐cube slices using wavelet‐domain hidden Markov trees

1999 ◽  
Author(s):  
Ivan Magrin‐Chagnolleau ◽  
Hyeokho Choi ◽  
Rutger van Spaendonck ◽  
Philippe Steeghs ◽  
Richard G. Baraniuk
Keyword(s):  
Hidden Markov ◽  
Texture Segmentation ◽  
Wavelet Domain ◽  
Hidden Markov Trees

Rotation-invariant texture retrieval using wavelet-based hidden Markov trees

2008 ◽  
Vol 88 (10) ◽  
pp. 2593-2598 ◽  
Author(s):  
Venkateswara Rao Rallabandi ◽  
V.P. Subramanyam Rallabandi
Keyword(s):  
Hidden Markov ◽  
Rotation Invariant ◽  
Texture Retrieval ◽  
Hidden Markov Trees

scholarly journals A framework based on hidden Markov trees for multimodal PET/CT image co-segmentation

2017 ◽  
Vol 44 (11) ◽  
pp. 5835-5848 ◽  
Author(s):  
Houda Hanzouli-Ben Salah ◽  
Jerome Lapuyade-Lahorgue ◽  
Julien Bert ◽  
Didier Benoit ◽  
Philippe Lambin ◽  
...  
Keyword(s):  
Hidden Markov ◽  
Ct Image ◽  
Pet Ct ◽  
Hidden Markov Trees

Oil Spill in SAR Image Denoising Method Based on Contourlet HMT

2012 ◽  
Vol 500 ◽  
pp. 545-549 ◽  
Author(s):  
Kun Liu ◽  
Xiao Feng Wang
Keyword(s):  
Oil Spill ◽  
Hidden Markov ◽  
Research Work ◽  
Speckle Reduction ◽  
Gray Level ◽  
Sar Image ◽  
Denoising Method ◽  
Image Denosing ◽  
Information Detection ◽  
Hidden Markov Trees

Contourlet domain hidden markov trees model was introduced in the SAR image denosing research work. Compared to the classical denosing method, the denoised SAR image can preserve information of oil spill and advantages for following up work. According to the gray level, this method segmented the SAR image to region of oil spill and ocean. Then using the method of Contourlet domain hidden markov trees model denoised the different regions. Experimental results show that the method represents better performance in speckle reduction and edges information detection.

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