Remote SensingDeep learning methods have shown significant advantages in polarimetric synthetic aperture radar (PolSAR) image classification. However, their performances rely on a large number of labeled data.
Jianlong Wang +6 more
doaj +1 more source
A Novel Multi-Objective Binary Chimp Optimization Algorithm for Optimal Feature Selection: Application of Deep-Learning-Based Approaches for SAR Image Classification. [PDF]
Sensors (Basel), 2023 Sadeghi F +4 more
europepmc +1 more source
Active Learning for PolSAR image classification
, 2013 One of the biggest problems, when supervised learning techniques are used, for training classifier, is the necessity of a big amount of labelled samples, including the problems and costs of carry out the labelling of the prototypes needed. SAR images are difficult to label due to the speckle noise, which increases the normal effort needed for labelling
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Estimation of the normalized coherency matrix through the SIRV model. Application to high resolution POLSAR data [PDF]
, 2009 8 pagesInternational audienceIn the context of non-Gaussian polarimetric clutter models, this paper presents an application of the recent advances in the field of Spherically Invariant Random Vectors (SIRV) modelling for coherency matrix estimation in ...
Gay, Michel +3 more
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Statistical Classification for Heterogeneous Polarimetric SAR Images
, 2011 International audienceThis paper presents a general approach for high-resolution polarimetric SAR data classification in heterogeneous clutter, based on a statistical test of equality of covariance matrices. The Spherically Invariant Random Vector (SIRV)
Ferro-Famil, Laurent +4 more
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Blind Source Separation in Polarimetric SAR Interferometry
, 2016 International audiencePolarimetric incoherent target decomposition aims in access-ing physical parameters of illuminated scatters through the analysis of target coherence or covariance matrix.
Pralon, Leandro, Vasile, Gabriel
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPolarimetric synthetic aperture radar (PolSAR) image classification is a critical application of remote sensing image interpretation. Most of the early algorithms that use hand-crafted features to divide the image into various scattering categories have ...
Yixin Zuo +3 more
doaj +1 more source
Self-Trained Deep Forest with Limited Samples for Urban Impervious Surface Area Extraction in Arid Area Using Multispectral and PolSAR Imageries. [PDF]
Sensors (Basel), 2022 Liu X +4 more
europepmc +1 more source
Marine Oil Spill Detection from SAR Images Based on Attention U-Net Model Using Polarimetric and Wind Speed Information. [PDF]
Int J Environ Res Public Health, 2022 Chen Y, Wang Z.
europepmc +1 more source
Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification
Remote SensingSuperpixel segmentation has been widely used in the field of computer vision. The generations of PolSAR superpixels have also been widely studied for their feasibility and high efficiency. The initial numbers of PolSAR superpixels are usually designed manually by experience, which has a significant impact on the final performance of superpixel ...
Boce Chu +7 more
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