PolSAR image classification with multiscale superpixel-based graph convolutional network
Convolutional neural networks (CNNs) have demonstrated impressive ability to achieve
promising results in PolSAR image classification. However, the traditional CNN performs …
promising results in PolSAR image classification. However, the traditional CNN performs …
Fusion and classification of SAR and optical data using multi-image color components with differential gradients
This paper proposes a gradient-based data fusion and classification approach for Synthetic
Aperture Radar (SAR) and optical image. This method is used to intuitively reflect the …
Aperture Radar (SAR) and optical image. This method is used to intuitively reflect the …
[HTML][HTML] PolSAR image land cover classification based on hierarchical capsule network
Polarimetric synthetic aperture radar (PolSAR) image classification is one of the basic
methods of PolSAR image interpretation. Deep learning algorithms, especially convolutional …
methods of PolSAR image interpretation. Deep learning algorithms, especially convolutional …
Improved remote sensing image classification based on multi-scale feature fusion
C Zhang, Y Chen, X Yang, S Gao, F Li, A Kong, D Zu… - Remote Sensing, 2020 - mdpi.com
When extracting land-use information from remote sensing imagery using image
segmentation, obtaining fine edges for extracted objects is a key problem that is yet to be …
segmentation, obtaining fine edges for extracted objects is a key problem that is yet to be …
A novel deep fully convolutional network for PolSAR image classification
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 …
more popular in recent years. As we all know, PolSAR image classification is actually a …
Interpretable POLSAR image classification based on adaptive-dimension feature space decision tree
Q Yin, J Cheng, F Zhang, Y Zhou, L Shao… - IEEE Access, 2020 - ieeexplore.ieee.org
Decision tree method has been applied to POLSAR image classification, due to its capability
to interpret the scattering characteristics as well as good classification accuracy. Compared …
to interpret the scattering characteristics as well as good classification accuracy. Compared …
Random neighbor pixel-block-based deep recurrent learning for polarimetric SAR image classification
Polarimetric synthetic aperture radar (PolSAR) image classification is an important part of
SAR data interpretation and provides more intuitive and detailed SAR polarization …
SAR data interpretation and provides more intuitive and detailed SAR polarization …
Optimal combination of polarimetric features for vegetation classification in PolSAR image
Polarimetric features of PolSAR images include inherent scattering mechanisms of terrain
types, which are important for classification and other Earth observation applications. By …
types, which are important for classification and other Earth observation applications. By …
Random region matting for the high-resolution polsar image semantic segmentation
Polarimetric synthetic aperture radar (PolSAR) imagery can provide more intuitive and
detailed SAR polarization information, and it is widely used in the classification and …
detailed SAR polarization information, and it is widely used in the classification and …
Integrating coordinate features in CNN-based remote sensing imagery classification
The land cover classification has played an important role in remote sensing applications.
However, most classification methods were designed based on the pixel features or local …
However, most classification methods were designed based on the pixel features or local …