Polarimetric SAR image segmentation based on spatially constrained kernel fuzzy C-means clustering

2015 ◽  
Author(s):  
Jianchao Fan ◽  
Jun Wang
Keyword(s):  
Image Segmentation ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Fuzzy C Means ◽  
Sar Image Segmentation ◽  
Fuzzy C Means Clustering

Robust non-local fuzzy c-means algorithm with edge preservation for SAR image segmentation

2013 ◽  
Vol 93 (2) ◽  
pp. 487-499 ◽  
Author(s):  
Jie Feng ◽  
L.C. Jiao ◽  
Xiangrong Zhang ◽  
Maoguo Gong ◽  
Tao Sun
Keyword(s):  
Image Segmentation ◽  
Sar Image ◽  
Edge Preservation ◽  
Fuzzy C Means ◽  
Sar Image Segmentation ◽  
Non Local ◽  
Fuzzy C Means Algorithm

scholarly journals Polarimetric SAR image segmentation with B-splines and a new statistical model

2010 ◽  
Vol 21 (4) ◽  
pp. 319-342 ◽  
Author(s):  
Alejandro C. Frery ◽  
Julio Jacobo-Berlles ◽  
Juliana Gambini ◽  
Marta E. Mejail
Keyword(s):  
Image Segmentation ◽  
Statistical Model ◽  
Sar Image ◽  
Polarimetric Sar ◽  
B Splines ◽  
Sar Image Segmentation

Polarimetric SAR Image Segmentation using CEM Algorithm

2014 ◽  
Vol 12 (5) ◽  
pp. 910-914
Author(s):  
Juan Ignacio Fernandez Michelli ◽  
Martin Hurtado ◽  
Javier Areta ◽  
Carlos Muravchik
Keyword(s):  
Image Segmentation ◽  
Sar Image ◽  
Polarimetric Sar ◽  
Sar Image Segmentation

scholarly journals SAR Image Segmentation Based on Improved Grey Wolf Optimization Algorithm and Fuzzy C-Means

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
M. Q. Li ◽  
L. P. Xu ◽  
Na Xu ◽  
Tao Huang ◽  
Bo Yan
Keyword(s):  
Image Segmentation ◽  
Differential Evolution ◽  
State Of The Art ◽  
Sar Image ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Fcm Algorithm ◽  
Fuzzy C Means ◽  
Sar Image Segmentation ◽  
Segmentation Approach

An improved Grey Wolf Optimization (GWO) algorithm with differential evolution (DEGWO) combined with fuzzy C-means for complex synthetic aperture radar (SAR) image segmentation was proposed for the disadvantages of traditional optimization and fuzzy C-means (FCM) in image segmentation precision. In the process of image segmentation based on FCM algorithm, the number of clusters and initial centers estimation is regarded as a search procedure that searches for an appropriate value in a greyscale interval. Hence, an improved differential evolution Grey Wolf Optimization (DE-GWO) algorithm is introduced to search for the optimal initial centers; then the image segmentation approach which bases its principle on FCM algorithm will get a better result. Experimental results in this work infers that both the precision and efficiency of the proposed method are superior to those of the state of the art.

Polarimetric SAR Image Segmentation Using Statistical Region Merging

2014 ◽  
Vol 11 (2) ◽  
pp. 509-513 ◽  
Author(s):  
Fengkai Lang ◽  
Jie Yang ◽  
Deren Li ◽  
Lingli Zhao ◽  
Lei Shi
Keyword(s):  
Image Segmentation ◽  
Sar Image ◽  
Region Merging ◽  
Polarimetric Sar ◽  
Sar Image Segmentation ◽  
Statistical Region Merging
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