Paper Info
Title
A High-Efficiency Automatic <inline-formula> <tex-math notation="LaTeX">$U$ </tex-math></inline-formula>-Distribution Segmentation Algorithm for PolSAR Images
Abstract
A fully automatic, non-Gaussian, and contextual clustering algorithm for segmentation of polarimetric synthetic aperture radar (SAR) images has been previously presented by Doulgeris. It achieved good results for both simulated and actual data sets. However, the long computation time was its main drawback. This letter discusses modifications to improve computational efficiency. The primary speed issues were rooted in the complicated probability density function (PDF) of the adopted model, for which evaluating the posterior probability of samples and estimating the parameters were both very time-consuming. We investigate the model parameters, reparametrize the model, and introduce lookup tables to speed up the processing chain. The new strategy speeds up both PDF evaluation and parameter estimation while maintaining the exactly similar visual results and now makes advanced non-Gaussian SAR image analysis a practical alternative.
Year
DOI
Venue
2019
10.1109/LGRS.2018.2881188
IEEE Geoscience and Remote Sensing Letters
Keywords
Field
DocType
Table lookup,Probability density function,Clustering algorithms,Synthetic aperture radar,Computational modeling,Covariance matrices,Image segmentation
Lookup table,Segmentation,Synthetic aperture radar,Algorithm,Image segmentation,Posterior probability,Estimation theory,Cluster analysis,Probability density function,Mathematics
Journal
Volume
Issue
ISSN
16
5
1545-598X
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Dingsheng Hu111.38
Anthony Paul Doulgeris211611.14
Xiaolan Qiu319026.75
Bin Lei4266.38
Yan Jin532.14