scholarly journals A novel feature descriptor for automatic change detection in remote sensing images

2019 ◽  
Vol 22 (2) ◽  
pp. 183-192 ◽  
Author(s):  
C.P. Dalmiya ◽  
N. Santhi ◽  
B. Sathyabama
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Feature Descriptor ◽  
Remote Sensing Images

scholarly journals A KERNEL-BASED SIMILARITY MEASURING FOR CHANGE DETECTION IN REMOTE SENSING IMAGES

2016 ◽  
Vol XLI-B7 ◽  
pp. 999-1006
Author(s):  
Xiaodan Shi ◽  
Guorui Ma ◽  
Fenge Chen ◽  
Yanli Ma
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Comparison Method ◽  
Kernel Functions ◽  
Multidimensional Data ◽  
Remote Sensing Images ◽  
Model Free ◽  
Change Vector ◽  
Similarity Measuring ◽  
Better Than

This paper presents a kernel-based approach for the change detection of remote sensing images. It detects change by comparing the probability density (PD), expressed as kernel functions, of the feature vector extracted from bi- temporal images. PD is compared by defined kernel functions without immediate PD estimation. This algorithm is model-free and it can process multidimensional data, and is fit for the images with rich texture in particular. Experimental results show that overall accuracy of the algorithm is 98.9 %, a little bit better than that of the change vector analysis and classification comparison method, which is 96.7 % and 95.9 % respectively.

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