Results 11 to 20 of about 505 (177)
Structure Label Matrix Completion for PolSAR Image Classification [PDF]
Remote Sensing, 2020 Terrain classification is a hot topic in polarimetric synthetic aperture radar (PolSAR) image interpretation that aims at assigning a label to every pixel and forms a label matrix for a PolSAR image.
Qian Wu +5 more
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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.
Boce Chu +7 more
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Despeckling PolSAR Images with a Structure Tensor Filter [PDF]
IEEE Geoscience and Remote Sensing Letters, 2020 © 2004-2012 IEEE. In this letter, we propose a new despeckling filter for fully polarimetric synthetic aperture radar (PolSAR) images defined by 3× 3 complex Wishart distributions. We first generalize the well-known structure tensor to deal with PolSAR data which allows to efficiently measure the dominant direction and contrast of edges.
Daniel Santana-Cedrés +3 more
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Random Ferns for Semantic Segmentation of PolSAR Images [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Random Ferns -- as a less known example of Ensemble Learning -- have been successfully applied in many Computer Vision applications ranging from keypoint matching to object detection. This paper extends the Random Fern framework to the semantic segmentation of polarimetric synthetic aperture radar images.
Pengchao Wei, Ronny Hänsch
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A Distribution Independent Ship Detector for PolSAR Images [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Ship detection with polarimetric synthetic aperture radar (PolSAR) images has attracted a lot of attention in recent years. However, modeling the distribution of clutter is a complicated task. This article introduces a distribution independent ship detector for PolSAR images. First, in order to improve the detection performance, the multichannel PolSAR
Zhou Xu 0002 +4 more
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Fisher Vectors for PolSAR Image Classification [PDF]
IEEE Geoscience and Remote Sensing Letters, 2017 In this letter, we study the application of the Fisher vector (FV) to the problem of pixelwise supervised classification of polarimetric synthetic aperture radar images. This is a challenging problem since information in those images is encoded as complex-valued covariance matrices. We observe that the real parts of these matrices preserve the positive
Javier A. Redolfi +2 more
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Feature Selection for Edge Detection in PolSAR Images
Remote Sensing, 2023 Edge detection is one of the most critical operations for moving from data to information. Finding edges between objects is relevant for image understanding, classification, segmentation, and change detection, among other applications. The Gambini Algorithm is a good choice for finding evidence of edges.
Anderson A. De Borba +3 more
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Classification of PolSAR Images by Stacked Random Forests [PDF]
ISPRS International Journal of Geo-Information, 2018 This paper proposes the use of Stacked Random Forests (SRF) for the classification of Polarimetric Synthetic Aperture Radar images. SRF apply several Random Forest instances in a sequence where each individual uses the class estimate of its predecessor as an additional feature. To this aim, the internal node tests are designed to work not only directly
Ronny Hänsch, Olaf Hellwich
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DESPECKLING POLSAR IMAGES BASED ON RELATIVE TOTAL VARIATION MODEL [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image.
C. Jiang +6 more
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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 +3 more
doaj +1 more source