Results 71 to 80 of about 505 (177)

MCDiff: A Multilevel Conditional Diffusion Model for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the swift advancement of deep learning, significant strides have been made in polarimetric synthetic aperture radar (PolSAR) image classification, particularly with the advent of diffusion models that allow for explicit class probability modeling ...
Qingyi Zhang, Xiaoxiao Fang, Tao Liu, Ronghua Wu, Liguo Liu, Chu He   +5 more
doaj   +1 more source

Semiparametric constant false alarm rate method for radar and sonar images

Electronics Letters, Volume 60, Issue 5, March 2024.
This study proposed a novel constant false alarm rate (CFAR) method based on Gaussian mixture model (GMM). The reason for starting this work is that some new polarimetric detectors and the high‐resolution cases may lead to the failure of traditional parametric model.
Ke Li, Peng Zhang, Ziyuan Yang
wiley   +1 more source

Fully Polarimetric SAR Image Filtering by Combining Block Matching and Lee Filter

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Speckle filtering is a key preprocessing approach for the applications of polarimetric synthetic aperture radar (PolSAR) data. Most current PolSAR filtering algorithms can hardly get good balance in suppressing speckle and retaining image details.
Guisheng Zhao, Shengyuan Zhu, Yinglei Wu
doaj   +1 more source

Semi-supervised PolSAR Image Classification Based on the Neighborhood Minimum Spanning Tree

Leida xuebao, 2019
In this paper, a novel semi-supervised classification method based on the Neighborhood Minimum Spanning Tree (NMST) is proposed to solve the Polarimetric Synthetic Aperture Radar (PolSAR) terrain classification when labeled samples are few. Combining the
HUA Wenqiang, WANG Shuang, GUO Yanhe, XIE Wen   +3 more
doaj   +1 more source

Semantic segmentation of PolSAR image data using advanced deep learning model. [PDF]

Sci Rep, 2021
Garg R, Kumar A, Bansal N, Prateek M, Kumar S.   +4 more
europepmc   +1 more source

BSDSNet: Dual-Stream Feature Extraction Network Based on Segment Anything Model for Synthetic Aperture Radar Land Cover Classification

Remote Sensing
Land cover classification using high-resolution Polarimetric Synthetic Aperture Radar (PolSAR) images obtained from satellites is a challenging task. While deep learning algorithms have been extensively studied for PolSAR image land cover classification,
Yangyang Wang, Wengang Zhang, Weidong Chen, Chang Chen   +3 more
doaj   +1 more source

Adaptive scale segmentation algorithm for polarimetric SAR image

The Journal of Engineering, 2019
Polarimetric SAR (PolSAR) data can be characterised by scattering matrix, which contains four elements. It is difficult to merge all the elements of the scattering matrix for segmentation.
Yifan Xu, Aifang Liu, Long Huang
doaj   +1 more source

Segmentation of polsar images

, 2017
This project will implement a segmentation algorithm for PolSAR images to represent the boundaries of the areas in the image and the regions. Identifying the regions on SAR images can be useful for further analysis, for example, to classify the elements of the image.
openaire   +1 more source

PolSAR Image Classification Via a Multigranularity Hybrid CNN-ViT Model With External Tokens and Cross-Attention

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the development of deep learning technology, the application of convolutional neural network (CNN) and vision transformer (ViT) for polarimetric synthetic aperture radar (PolSAR) image classification has been deepened.
Wenke Wang, Jianlong Wang, Dou Quan, Meijuan Yang, Junding Sun, Bibo Lu   +5 more
doaj   +1 more source

Semi-Supervised Classification of PolSAR Images Based on Co-Training of CNN and SVM with Limited Labeled Samples. [PDF]

Sensors (Basel), 2023
Zhao M, Cheng Y, Qin X, Yu W, Wang P.
europepmc   +1 more source