scholarly journals Selection of the Optimal Segmentation Scale in High-resolution Remote Sensing Image

2018 ◽  
Author(s):  
Yi-xian CHENG ◽  
Feng MAO
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Image ◽  
Optimal Segmentation ◽  
Selection Of

Optimal segmentation of a high-resolution remote-sensing image guided by area and boundary

2014 ◽  
Vol 35 (19) ◽  
pp. 6914-6939 ◽  
Author(s):  
Jie Chen ◽  
Min Deng ◽  
Xiaoming Mei ◽  
Tieqiao Chen ◽  
Quanbin Shao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Image ◽  
Image Guided ◽  
Optimal Segmentation

scholarly journals ARCHETYPAL ANALYSIS: AN ALTERNATIVE TO CLUSTERING FOR UNSUPERVISED TEXTURE SEGMENTATION

2019 ◽  
Vol 38 (2) ◽  
pp. 151 ◽  
Author(s):  
Ismael Cabero ◽  
Irene Epifanio
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Image ◽  
Texture Segmentation ◽  
Textural Features ◽  
Archetypal Analysis ◽  
Natural Landscapes ◽  
High Resolution Images ◽  
Selection Of

Texture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The proposed procedure has been tested on a remote sensing image application with local granulometries, providing promising results.

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