The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

2015 ◽  
Author(s):  
Xi Chen ◽  
Liqing Zhou
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Parallel Processing ◽  
Mean Shift ◽  
Remote Sensing Image ◽  
Mean Shift Algorithm

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

An Improved Mean Shift Segmentation Method of High-Resolution Remote Sensing Image Based on LBP and Canny Features

2015 ◽  
Vol 713-715 ◽  
pp. 1589-1592
Author(s):  
Yong Li ◽  
Jing Wen Xu ◽  
Jun Fang Zhao ◽  
Yu Dan Zhao ◽  
Xin Li
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Mean Shift ◽  
Feature Space ◽  
Remote Sensing Image ◽  
Medical Image Segmentation ◽  
Segmentation Method ◽  
Mean Shift Algorithm ◽  
Segmentation Accuracy ◽  
Fuzzy Boundary

Mean shift algorithm is a robust approach toward feature space analysis, which has been wildly used for natural scene image and medical image segmentation. Due to fuzzy boundary and low accuracy of Mean shift segmentation method, this paper puts forward to an improved Mean shift segmentation method of high-resolution remote sensing image based on LBP and Canny features. The results show that this improved Mean shift segmentation access can enhance segmentation accuracy compared to the traditional Mean shift.

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