A Novel Change Detection Method Based on Statistical Distribution Characteristics Using Multi-Temporal PolSAR Data
Unsupervised change detection approaches, which are relatively straightforward and easy to implement and interpret, and which require no human intervention, are widely used in change detection. Polarimetric synthetic aperture radar (PolSAR), which has an all-weather response capability with increase...
Main Authors: | Jinqi Zhao, Yonglei Chang, Jie Yang, Yufen Niu, Zhong Lu, Pingxiang Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/5/1508 |
Similar Items
-
An Unsupervised Method of Change Detection in Multi-Temporal PolSAR Data Using a Test Statistic and an Improved K&I Algorithm
by: Jinqi Zhao, et al.
Published: (2017-12-01) -
A Novel Method of Change Detection in Bi-Temporal PolSAR Data Using a Joint-Classification Classifier Based on a Similarity Measure
by: Jinqi Zhao, et al.
Published: (2017-08-01) -
Unsupervised Change Detection Using Multi-Temporal SAR Data : A Case Study of Arctic Sea Ice
by: Fröjse, Linda
Published: (2014) -
An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3
by: Wensong Liu, et al.
Published: (2018-02-01) -
Edge Detection of PolSAR Image Based on Stochastic Distance
by: WANG Qing, et al.
Published: (2015-07-01)