Results 21 to 30 of about 5,464 (214)
Remote Sensing, 2023 Recently, deep learning methods have been widely studied in the field of polarimetric synthetic aperture radar (PolSAR) ship detection. However, extracting polarimetric and spatial features on the whole PolSAR image will result in high computational ...
Weixing Qiu, Zongxu Pan
doaj +1 more source
Analytic Expressions for Stochastic Distances Between Relaxed Complex Wishart Distributions [PDF]
, 2013 The scaled complex Wishart distribution is a widely used model for multilook full polarimetric SAR data whose adequacy has been attested in the literature.
Cintra, Renato J. +2 more
core +1 more source
Earth and Space Science, Volume 10, Issue 6, June 2023., 2023 Abstract The polarimetric Synthetic Aperture Radar (SAR) data sets have been widely exploited for land use land cover (LULC) classification due to their sensitivity to the structural and dielectric properties of the imaging target. In this study, the potential of fully polarimetric L‐ and S‐band Airborne SAR (LS‐ASAR) data sets were explored for the ...
Shatakshi Verma +2 more
wiley +1 more source
A deep-neural-network-based hybrid method for semi-supervised classification of polarimetric SAR data [PDF]
, 2019 This paper proposes a deep-neural-network-based semi-supervised method for polarimetric synthetic aperture radar (PolSAR) data classification. The proposed method focuses on achieving a well-trained deep neural network (DNN) when the amount of the ...
Huang, Shaoguang +4 more
core +1 more source
Feature fusion method based on local binary graph for PolSAR image classification
IET Radar, Sonar &Navigation, Volume 17, Issue 6, Page 939-954, June 2023., 2023 We propose a novel supervised version of GCNs named mini‐GCNs, for short. As the name suggests, mini‐GCNs can be trained in mini‐batch fashion, trying to achieve a better and more robust local optimum. To remove the redundant information extracted from the designed CNN and mini‐GCN, a feature fusion method is proposed to achieve better classification ...
Mohammad Ali Sebt, Mohsen Darvishnezhad
wiley +1 more source
Optimum graph cuts for pruning binary partition trees of polarimetric SAR images [PDF]
, 2016 This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images.
Foucher, Samuel +1 more
core +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment.
Feng Zhao +3 more
doaj +1 more source
Remote Sensing, 2022 The radiometric terrain correction (RTC) is an essential processing step for supervised classification applications of polarimetric synthetic aperture radar (PolSAR) over mountainous areas.
Lei Zhao +4 more
doaj +1 more source
On the use of the l(2)-norm for texture analysis of polarimetric SAR data [PDF]
, 2016 In this paper, the use of the l2-norm, or Span, of the scattering vectors is suggested for texture analysis of polarimetric synthetic aperture radar (SAR) data, with the benefits that we need neither an analysis of the polarimetric channels separately ...
Deng, xinping, López Martínez, Carlos
core +2 more sources
Optical images-based edge detection in Synthetic Aperture Radar images [PDF]
, 2015 We address the issue of adapting optical images-based edge detection techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery. We modify the gravitational edge detection technique (inspired by the Law of Universal Gravity) proposed by
Barrenechea, Edurne +5 more
core +2 more sources