A Novel Method of Change Detection in Bi-Temporal PolSAR Data Using a Joint-Classification Classifier Based on a Similarity Measure

A Novel Method of Change Detection in Bi-Temporal PolSAR Data Using a Joint-Classification Classifier Based on a Similarity Measure

Accurate and timely change detection of the Earth’s surface features is extremely important for understanding the relationships and interactions between people and natural phenomena. Owing to the all-weather response capability, polarimetric synthetic aperture radar (PolSAR) has become a key tool fo...

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Bibliographic Details
Main Authors: Jinqi Zhao, Jie Yang, Zhong Lu, Pingxiang Li, Wensong Liu, Le Yang
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Remote Sensing
Subjects:
change detection
joint-classification classifier
similarity measure
test statistic
Kittler and Illingworth (K &amp
I) threshold segmentation
PolSAR
Online Access:https://www.mdpi.com/2072-4292/9/8/846

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https://www.mdpi.com/2072-4292/9/8/846

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