Results 71 to 80 of about 840 (174)
CV-CPKAN: Complex-Valued Convolutional Kolmogorov–Arnold Framework for PolSAR Image Classification
Remote SensingDeep learning has significantly advanced PolSAR image processing, with a growing trend of integrating mathematical theories into deep neural networks to enhance their capabilities with regard to complex data.
Zuzheng Kuang +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 +2 more sources
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
A Review on PolSAR for FOPEN Applications
Abstract: PolSAR has become a significant focus of research due to its wide-ranging applications in structural monitoring, foliage penetration, and target detection. Despite its potential, work on FOPEN remains limited and often inconsistent, largely because forest environments differ considerably in structure and density. Integrating PolSAR with FOPEN
Afaan Shaikh +5 more
openaire +4 more sources
Classification for Polsar image based on hölder divergences
The Journal of Engineering, 2019 (Dis)similarity measures play an important role in the interpretation of polarimetric synthetic aperture radar (PolSAR) images. Here, the authors introduce a kind of similarity measures for PolSAR images based on the concepts of Hölder pseudo-divergence ...
Ting Pan +4 more
doaj +1 more source
Remote SensingPolSAR image classification has attracted extensive significant research in recent decades. Aiming at improving PolSAR classification performance with speckle noise, this paper proposes an active complex-valued convolutional-wavelet neural network by ...
Lu Liu, Yongxiang Li
doaj +1 more source
Adversarial Reconstruction-Classification Networks for PolSAR Image Classification
Remote Sensing, 2019 Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely used in recent years. It is well known that PolSAR image classification is a dense prediction problem. The recently proposed fully convolutional networks (
Yanqiao Chen +5 more
doaj +1 more source
Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests
Remote Sensing, 2017 Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests.
Oleg Antropov +3 more
doaj +1 more source
Remote SensingLimited labels and detailed changed land-cover interpretation requirements pose challenges for time-series PolSAR change monitoring research. Accurate labels and supervised models are difficult to reuse between massive unlabeled time-series PolSAR data ...
Xinyue Zhang +5 more
doaj +1 more source
Prototype Theory Based Feature Representation for PolSAR Images
Leida xuebao, 2016 This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory.
Huang Xiaojing +3 more
doaj +1 more source