Remote Sensing Image Segmentation Using Mean Shift Method

2011 ◽  
pp. 86-90 ◽  
Author(s):  
Fang Wan ◽  
Fei Deng
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Mean Shift ◽  
Remote Sensing Image ◽  
Shift Method

Research of Remote Sensing Image Segmentation Based on Mean Shift and Region Merging

2011 ◽  
Vol 90-93 ◽  
pp. 2836-2839 ◽  
Author(s):  
Jian Cui ◽  
Dong Ling Ma ◽  
Ming Yang Yu ◽  
Ying Zhou
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Large Scale ◽  
Mean Shift ◽  
Image Features ◽  
Small Scale ◽  
Region Merging ◽  
Segmentation Method ◽  
Shift Method ◽  
Scale Parameters

In order to extract ground information more accurately, it is important to find an image segmentation method to make the segmented features match the ground objects. We proposed an image segmentation method based on mean shift and region merging. With this method, we first segmented the image by using mean shift method and small-scale parameters. According to the region merging homogeneity rule, image features were merged and large-scale image layers were generated. What’s more, Multi-level image object layers were created through scaling method. The test of segmenting remote sensing images showed that the method was effective and feasible, which laid a foundation for object-oriented information extraction.

Improved fast mean shift algorithm for remote sensing image segmentation

2015 ◽  
Vol 9 (5) ◽  
pp. 389-394 ◽  
Author(s):  
Jia-Xiang Zhou ◽  
Zhi-Wei Li ◽  
Chong Fan
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Mean Shift ◽  
Remote Sensing Image ◽  
Mean Shift Algorithm

scholarly journals Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation

2009 ◽  
pp. 257-264 ◽  
Author(s):  
Filiberto Pla ◽  
Gema Gracia ◽  
Pedro García-Sevilla ◽  
Majid Mirmehdi ◽  
Xianghua Xie
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Remote Sensing Image
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