Results 21 to 30 of about 2,015 (220)

A Novel Deep Fully Convolutional Network for PolSAR Image Classification

Remote Sensing, 2018
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular in recent years. As we all know, PolSAR image classification is actually a dense prediction problem.
Yangyang Li, Yanqiao Chen, Guangyuan Liu, Licheng Jiao   +3 more
doaj   +1 more source

Convolutional Kernel‐based covariance descriptor for classification of polarimetric synthetic aperture radar images

IET Radar, Sonar & Navigation, 2022
There are two types of important information in a polarimetric synthetic aperture radar (PolSAR) image: spatial features in two dimensions and polarimetric characteristics in the scattering dimension. Considering both polarimetric and spatial information
Maryam Imani
doaj   +1 more source

Deep support vector machine for PolSAR image classification

International Journal of Remote Sensing, 2021
The main problem posed by Polarimetric Synthetic Aperture Radar (PolSAR) image classification in remote sensing is the ability to develop classifiers that can substantially discern the different classes inherent in natural and man-made targets. Emphasis has shifted from the use of conventional classifiers to modern non-parametric classifiers such as ...
Onuwa Okwuashi, Christopher E. Ndehedehe, Dupe Nihinlola Olayinka, Aniekan Eyoh, Hosanna Attai   +4 more
openaire   +2 more sources

Terrain effect analysis and compensation method for polarimetric synthetic aperture radar interferometry height parameter inversion

IET Radar, Sonar &Navigation, Volume 16, Issue 12, Page 1924-1935, December 2022., 2022
Abstract In this paper, the terrain effect on parameter inversion performance of polarimetric synthetic aperture radar (PolSAR) and polarimetric SAR interferometry (PolInSAR) are analysed first. Based on the analysis of the terrain effect on single pixel processing, the terrain effect between adjacent pixels is addressed for both PolSAR and PolInSAR ...
Suo Zhiyong, Wang Tingting, Xue Chao, Zhang Tao   +3 more
wiley   +1 more source

Classification of Polarimetric SAR Images Based on the Riemannian Manifold

Leida xuebao, 2017
Classification is one of the core components in the interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. A new PolSAR image classification approach employs the structural properties of the Riemannian manifold formed by PolSAR ...
Yang Wen, Zhong Neng, Yan Tianheng, Yang Xiangli   +3 more
doaj   +1 more source

A Novel Multi-Feature Joint Learning Method for Fast Polarimetric SAR Terrain Classification

IEEE Access, 2020
Polarimetric synthetic aperture radar (PolSAR) image classification is one of the most important study areas for PolSAR image processing. Many kinds of PolSAR features can be extracted for PolSAR image classification, such as the scattering, polarimetric
Junfei Shi, Haiyan Jin, Xiaohua Li
doaj   +1 more source

Spatial and polarimetric information fusion using residual network for polarimetric synthetic aperture radar image classification

IET Radar, Sonar &Navigation, Volume 16, Issue 12, Page 1963-1976, December 2022., 2022
Abstract A polarimetric synthetic aperture radar (POLSAR) system provides an image that can be considered as a data cube containing spatial information in two spatial dimensions and polarimetric information in the scattering dimension. A spatial and polarimetric residual network (SPRN) is proposed for POLSAR image classification. At first, polarimetric
Maryam Imani
wiley   +1 more source

The Importance of Lake Emergent Aquatic Vegetation for Estimating Arctic‐Boreal Methane Emissions

Journal of Geophysical Research: Biogeosciences, Volume 127, Issue 6, June 2022., 2022
Abstract Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under‐represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ∼1.5 m deep and can be detected with synthetic aperture radar (SAR). To assess the importance of lake emergent
Ethan D. Kyzivat, Laurence C. Smith, Fenix Garcia‐Tigreros, Chang Huang, Chao Wang, Theodore Langhorst, Jessica V. Fayne, Merritt E. Harlan, Yuta Ishitsuka, Dongmei Feng, Wayana Dolan, Lincoln H Pitcher, Kimberly P. Wickland, Mark M. Dornblaser, Robert G. Striegl, Tamlin M. Pavelsky, David E. Butman, Colin J. Gleason   +17 more
wiley   +1 more source

A Novel Classification Method for PolSAR Image Combining the Deep Learning Model and Adaptive Boosting of Shallow Classifiers

Canadian Journal of Remote Sensing, 2023
Polarimetric synthetic aperture radar (PolSAR) images are classified mainly according to the backscattering information of ground objects. For regions with complex backscattering information, misclassification is easy to occur, which leads to challenges ...
Yan Duan, Shaojie Bai, Limin Liu, Guangwei Wang   +3 more
doaj   +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, Salembier Clairon, Philippe Jean   +1 more
core   +2 more sources