Results 91 to 100 of about 7,181 (241)

Unsupervised PolSAR Image Classification Based on Superpixel Pseudo-Labels and a Similarity-Matching Network

Remote Sensing
Supervised polarimetric synthetic aperture radar (PolSAR) image classification demands a large amount of precisely labeled data. However, such data are difficult to obtain.
Lei Wang, Lingmu Peng, Rong Gui, Hanyu Hong, Shenghui Zhu   +4 more
doaj   +1 more source

Iterative Bilateral Filtering of Polarimetric SAR Data

, 2013
In this paper, we introduce an iterative speckle filtering method for polarimetric SAR (PolSAR) images based on the bilateral filter. To locally adapt to the spatial structure of images, this filter relies on pixel similarities in both spatial and ...
D'Hondt, Olivier, Guillaso, Stéphane, Hellwich, Olaf   +2 more
core   +1 more source

Comparison of PolSAR Speckle Filtering Techniques [PDF]

2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
The objective of this paper is to compare the most widely used and the most recent speckle polarimetric synthetic aperture radar (PolSAR) filters. Two new conceptual approaches in PolSAR filtering are evaluated on simulated PolSAR images. The criteria of comparison includes indicator of speckle reduction capability, edge sharpness and preservation of ...
G. Farage, S. Foucher, G. Benie
openaire   +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

Unsupervised Classification for Polarimetric Synthetic Aperture Radar Images Based on Wishart Mixture Models

Leida xuebao, 2017
Unsupervised classification is a significant step inthe automated interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, determining the number of clusters in this process is still a challenging problem. To this end, we propose
Zhong Neng, Yang Wen, Yang Xiangli, Guo Wei   +3 more
doaj   +1 more source

A novel self‐supervised ensemble learning framework for land use and land cover classification of polarimetric synthetic aperture radar images

IET Radar, Sonar &Navigation, Volume 18, Issue 3, Page 379-409, March 2024.
The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. Also, the designed deep learning model can obtain the effective features of homogeneous samples gathering together and heterogeneous samples separating from each other in a self‐supervised manner.
Mohsen Darvishnezhad, Mohammad Ali Sebt
wiley   +1 more source

Heterogeneous Network-Based Contrastive Learning Method for PolSAR Land Cover Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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 PolSAR
Jianfeng Cai, Yue Ma, Zhixi Feng, Shuyuan Yang, Licheng Jiao   +4 more
doaj   +1 more source

CFAR-Based Adaptive PolSAR Speckle Filter

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018
The patch-based polarimetric synthetic aperture radar (PolSAR) nonlocal means (NLM) speckle filters are efficacious in noise suppression and detail preservation, but are computationally inefficient. The objective of this paper is to develop a filter that provides better noise suppression and edge preservation along with reduced computational complexity
Rakesh Sharma, Rajib Kumar Panigrahi
openaire   +1 more source

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Earth and Space Science, Volume 11, Issue 1, January 2024.
Abstract The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height,
Dharanya Thulasiraman, Dipanwita Haldar, Shashi Kumar, Arun Balaji Ramathilagam, N. R. Patel   +4 more
wiley   +1 more source

Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification

Remote Sensing
Superpixel 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, Mengxuan Zhang, Kun Ma, Long Liu, Junwei Wan, Jinyong Chen, Jie Chen, Hongcheng Zeng   +7 more
doaj   +1 more source