Results 31 to 40 of about 505 (177)

Joint Polarimetric-Adjacent Features Based on LCSR for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Image classification is a critical and important application in PolSAR image interpretation. Finding a feature extraction method, which can effectively describe the characteristics of the target, is an important basis for image classification.
Xiao Wang, Lamei Zhang, Ning Wang, Bin Zou   +3 more
doaj   +1 more source

Speeding up Non-Gaussian POLSAR image analysis [PDF]

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Non-Gaussian statistical models fit SAR data better than Gaussian-based statistics, in most cases, but are complicated and time-consuming to use for unsupervised image segmentation via probabilistic clustering. The more advanced the model, the more complicated and slow the clustering.
Doulgeris, Anthony Paul, Hu, Dingsheng
openaire   +3 more sources

DNN-Based PolSAR Image Classification on Noisy Labels

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
This work was supported in part by the National Natural Science Foundation of China under Grant 61871413 and Grant 61801015, in part by the Fundamental Research Funds for the Central Universities under Grant XK2020-03, in part by China Scholarship Council under Grant 2020006880033, and in part by Grant PID2020-114623RB-C32 funded by MCIN/AEI/10.13039 ...
Jun Ni, Deliang Xiang, Zhiyuan Lin, Carlos López-Martínez, Wei Hu 0004, Fan Zhang 0007   +5 more
openaire   +3 more sources

Your Input Matters—Comparing Real-Valued PolSAR Data Representations for CNN-Based Segmentation

Remote Sensing, 2023
Inspired by the success of Convolutional Neural Network (CNN)-based deep learning methods for optical image segmentation, there is a growing interest in applying these methods to Polarimetric Synthetic Aperture Radar (PolSAR) data.
Sylvia Hochstuhl, Niklas Pfeffer, Antje Thiele, Horst Hammer, Stefan Hinz   +4 more
doaj   +1 more source

PolSAR Image Classification Based on Statistical Distribution and MRF [PDF]

Remote Sensing, 2020
Classification is an important topic in synthetic aperture radar (SAR) image processing and interpretation. Because of speckle and imaging geometrical distortions, land cover mapping is always a challenging task especially in complex landscapes.
Junjun Yin 0001, Xiyun Liu, Jian Yang 0011, Chih-Yuan Chu 0002, Yang-Lang Chang   +4 more
openaire   +3 more sources

Low frequency and radar’s physical based features for improvement of convolutional neural networks for PolSAR image classification

Egyptian Journal of Remote Sensing and Space Sciences, 2022
Although various deep neural networks such as convolutional neural networks (CNNs) have been suggested for classification of polarimetric synthetic aperture radar (PolSAR) images, but, they have several deficiencies.
Maryam Imani
doaj   +1 more source

Robust Classification of PolSAR Images Based on Pinball loss Support Vector Machine

Leida xuebao, 2019
Given the problems that the amount of supervised information in the Polarimetric Synthetic Aperture Radar (PolSAR) image is low and the speckle noise is difficult to eliminate, in this study, a robust classification algorithm for PolSAR image based on ...
ZHANG Lamei, ZHANG Siyu, DONG Hongwei, ZHU Sha   +3 more
doaj   +1 more source

Semi-supervised PolSAR Image Change Detection using Similarity Matching [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
The lack of precisely labeled data limits the development of supervised polarimetric synthetic aperture radar (PolSAR) image change detection. Therefore, semi-supervised deep learning methods have recently demonstrated their significant capability for ...
L. Wang, L. Peng, H. Hong, S. Zhao, Q. Lv, R. Gui   +5 more
doaj   +1 more source

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

Observation and Coordination Needs for Current, Near‐Future, and Next Generation Earth‐Observing SAR Systems

Earth and Space Science, Volume 13, Issue 5, May 2026.
Abstract This paper summarizes an evaluation by experts of how coordination of Earth‐observing Synthetic Aperture Radar (SAR) missions among the world's space agencies could advance toward game‐changing scientific discoveries and fully realizing SAR's practical capability to address many issues facing society.
Cathleen E. Jones, Ake Rosenqvist, Björn Rommen, Magdalena Fitrzyk, Eric Rignot, Bernd Scheuchl, Yujie Zheng, Andrew Hooper, Mark Simons, Tomokazu Kobayashi, Paul Siqueira, Maurizio Santoro, Takeo Tadono, Laura Hess, Heather McNairn, Laura Frulla, Malin Johansson, Wolfgang Dierking, Line Rouyet, Annett Bartsch, Paco Lopez Dekker, Johnny A. Johannessen   +21 more
wiley   +1 more source