Adaptive Laplacian eigenmap-based dimension reduction for ocean target discrimination
It is well known that polarimetric synthetic aperture radar (PolSAR) backscattering features
are highly influenced by the variation of incidence angle (VIA), which usually hampers the …
are highly influenced by the variation of incidence angle (VIA), which usually hampers the …
Laplacian eigenmaps-based polarimetric dimensionality reduction for SAR image classification
In this paper, we propose a novel scheme of polarimetric synthetic aperture radar (PolSAR)
image classification. We apply Laplacian eigenmaps (LE), a nonlinear dimensionality …
image classification. We apply Laplacian eigenmaps (LE), a nonlinear dimensionality …
Supervised polarimetric SAR image classification using tensor local discriminant embedding
Feature extraction is a very important step for polarimetric synthetic aperture radar (PolSAR)
image classification. Many dimensionality reduction (DR) methods have been employed to …
image classification. Many dimensionality reduction (DR) methods have been employed to …
Supervised locally linear embedding for polarimetric sar image classification
H Cao, H Zhang, C Wang, M Liu - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
In this paper the Supervised Locally Linear Embedding (SLLE) algorithm is introduced into
polarimetric SAR (PolSAR) feature dimensionality reduction (DR) and land cover …
polarimetric SAR (PolSAR) feature dimensionality reduction (DR) and land cover …
The potential of linear discriminative Laplacian eigenmaps dimensionality reduction in polarimetric SAR classification for agricultural areas
In this paper, the linear discriminative Laplacian eigenmaps (LDLE) dimensionality
reduction (DR) algorithm is introduced to C-band polarimetric synthetic aperture radar …
reduction (DR) algorithm is introduced to C-band polarimetric synthetic aperture radar …
PolSAR ship detection using local scattering mechanism difference based on regression kernel
J He, Y Wang, H Liu, N Wang - IEEE Geoscience and Remote …, 2017 - ieeexplore.ieee.org
In this letter, the local scattering mechanism difference based on regression kernel
(LSMDRK) is developed as a discriminative feature for ship detection. The LSMDRK …
(LSMDRK) is developed as a discriminative feature for ship detection. The LSMDRK …
A Novel Polarization Scattering Decomposition Model and Its Application to Ship Detection
L Fang, Z Yang, W Mu, T Liu - Remote Sensing, 2023 - mdpi.com
In polarimetric synthetic aperture radar (POLSAR), it is of great significance for civil and
military applications to find novel model-based decomposition methods suitable for ship …
military applications to find novel model-based decomposition methods suitable for ship …
Feature selection and weighted SVM classifier-based ship detection in PolSAR imagery
X Xing, K Ji, H Zou, J Sun - International Journal of Remote …, 2013 - Taylor & Francis
Target decomposition is an important method for ship detection in polarimetric synthetic
aperture radar (SAR) imagery. Parameters such as the polarization entropy and alpha angle …
aperture radar (SAR) imagery. Parameters such as the polarization entropy and alpha angle …
Classification of man-made targets via invariant coherency-matrix eigenvector decomposition of polarimetric SAR/ISAR images
R Paladini, M Martorella… - IEEE transactions on …, 2011 - ieeexplore.ieee.org
In this paper, the problem of classifying nonhomogeneous man-made targets is investigated
by performing a macroscopic and detailed target analysis. The Cloude-Pottier H/α ML …
by performing a macroscopic and detailed target analysis. The Cloude-Pottier H/α ML …
Nearest-regularized subspace classification for PolSAR imagery using polarimetric feature vector and spatial information
Feature extraction using polarimetric synthetic aperture radar (PolSAR) images is of great
interest in SAR classification, no matter if it is applied in an unsupervised approach or a …
interest in SAR classification, no matter if it is applied in an unsupervised approach or a …