A novel framework for change detection in bi-temporal polarimetric SAR images

2016 ◽  
Author(s):  
Davide Pirrone ◽  
Francesca Bovolo ◽  
Lorenzo Bruzzone
Keyword(s):  
Change Detection ◽  
Polarimetric Sar ◽  
Sar Images

Change detection of polarimetric SAR images based on the KummerU Distribution

2014 ◽  
Author(s):  
Quan Chen ◽  
Pengfei Zou ◽  
Zhen Li ◽  
Ping Zhang
Keyword(s):  
Change Detection ◽  
Polarimetric Sar ◽  
Sar Images

scholarly journals Change Detection in Time Series of Polarimetric SAR Images

2021 ◽  
pp. 35-71
Author(s):  
Knut Conradsen ◽  
Henning Skriver ◽  
Morton J. Canty ◽  
Allan A. Nielsen
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Polarimetric Sar ◽  
Sar Images

scholarly journals AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

2016 ◽  
Vol XLI-B7 ◽  
pp. 611-615
Author(s):  
J. Q. Zhao ◽  
J. Yang ◽  
P. X. Li ◽  
M. Y. Liu ◽  
Y. M. Shi
Keyword(s):  
Change Detection ◽  
Detection Method ◽  
Speckle Noise ◽  
Natural Phenomena ◽  
Threshold Selection ◽  
Test Statistic ◽  
Polarimetric Sar ◽  
Sar Images ◽  
Multi Temporal ◽  
Selection Of

Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

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