Zobrazeno 1 - 10
of 439
pro vyhledávání: '"PolSAR image"'
Publikováno v:
In Applied Soft Computing February 2025 170
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16433-16448 (2024)
Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classification. Supervised learning (SL) requires a large amount of labeled Po
Externí odkaz:
https://doaj.org/article/9fb9630afdf44caba10a73170b6f8aff
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11451-11466 (2024)
Polarimetric 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 h
Externí odkaz:
https://doaj.org/article/74290d01539646cabb58e18c116cc7ac
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 11503-11520 (2024)
The scattering properties of targets in polarimetric synthetic aperture radar (PolSAR) images are directly influenced by the targets' orientations, as the scattering properties from the same target with different orientations can be very different. T
Externí odkaz:
https://doaj.org/article/27602b699ee1403a98d18e1150fa1925
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10842-10861 (2024)
Due to the interference of multiplicative speckles, it is challenging to accurately detect changes in polarimetric synthetic aperture radar (PolSAR) images. Convolutional neural network has been proven to learn rich local features from PolSAR data. H
Externí odkaz:
https://doaj.org/article/441926ce1f23407f9def3a482d32dcd7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10203-10220 (2024)
The sensitivity and dependence of polarization and scattering on target orientation and radar incident angle pose a significant challenge in interpreting polarimetric synthetic aperture radar (PolSAR) images. Previous studies have emphasized the pote
Externí odkaz:
https://doaj.org/article/46597637d2134a399621c1980667eed9
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 8527-8542 (2024)
Vision transformer (ViT) provides new ideas for polarization synthetic aperture radar (PolSAR) image classification due to its advantages in learning global-spatial information. However, the lack of local-spatial information within samples and correl
Externí odkaz:
https://doaj.org/article/9b0a96f965af4e25b0d323b7b62ccfdf
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4829-4844 (2024)
Dihedral is a common structure in polarimetric SAR images and can be found on many man-made targets. Many researchers have proposed different dihedral models, but the accuracy of these models is limited. In this case, the feature extraction methods b
Externí odkaz:
https://doaj.org/article/324d1084ce1140fb8d251e509958ad09
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3727-3741 (2024)
Polarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation. Various types and siz
Externí odkaz:
https://doaj.org/article/85ed3b75649642c79713d86a93e1ef4b
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103706- (2024)
Deep neural networks have recently been extensively utilized for Polarimetric synthetic aperture radar (PolSAR) image classification. However, this heavily relies on extensive labeled data which is both costly and labor-intensive. To lower the collec
Externí odkaz:
https://doaj.org/article/c9d3d4361c7e47d7a317098573d08590