PolSAR Image Speckle Reduction Based on Classification of Similarity Features Between Coherency Matrices

A novel PolSAR image speckle reduction algorithm based on a new definition of similarity coefficient is proposed in this paper. Pixels in image are firstly classified into three types by threshold segmentation which is calculated with the similarity features. Then, weighted filtering is applied on t...

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Published in:IEEE access 2019, Vol.7, p.136986-136994
Main Authors: Han, Ping, Dong, Fei, Jia, Kun, Han, Binbin
Format: Article
Language:English
Subjects:
Algorithms
Coherence
Covariance matrices
Image classification
Image segmentation
Lee Filter
Mathematical model
Matrix decomposition
pixel classification
Pixels
Polarimetry
PolSAR image
Reduction
similarity coefficient
Speckle
speckle reduction
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container_title IEEE access
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creator Han, Ping
Dong, Fei
Jia, Kun
Han, Binbin
description A novel PolSAR image speckle reduction algorithm based on a new definition of similarity coefficient is proposed in this paper. Pixels in image are firstly classified into three types by threshold segmentation which is calculated with the similarity features. Then, weighted filtering is applied on the pixels selected according to their types, power features and similarity properties. Experimental results with measured data collected by NASA/JPL AIRSAR system show that the proposed method is more effective than Lee Filter not only in speckle suppression but also in polarimetric properties and structure feature preservation.
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source IEEE Xplore Open Access Journals
subjects Algorithms
Coherence
Covariance matrices
Image classification
Image segmentation
Lee Filter
Mathematical model
Matrix decomposition
pixel classification
Pixels
Polarimetry
PolSAR image
Reduction
similarity coefficient
Speckle
speckle reduction
title PolSAR Image Speckle Reduction Based on Classification of Similarity Features Between Coherency Matrices
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