Results 211 to 220 of about 7,181 (241)

ICA based PolSAR image denoising

2016 12th IEEE International Symposium on Electronics and Telecommunications (ISETC), 2016
A speckle denoising in polarimetric SAR images is proposed considering as filtering method the sparse code shrinkage algorithm based on ICA. Even thou the ICA method was widely used in audio signal processing, in combination with shrinkage function give good results for multiplicative noise reduction. The Extended Generalized Lambda Distribution (EGLD)
Raul Malutan, Romulus Terebes, Mihaela Cislariu, Christian Germain, Ioana Ilea   +4 more
openaire   +1 more source

Jamming suppression in Dual-channel PolSAR

2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar, 2009
In the paper, we provide a method to suppress both the blanketing jamming and the deceptive jamming in Dual-channel PolSAR (D-PolSAR) system. The model of the signal and jamming in the D-PolSAR system is analyzed. By comparing the difference between jamming and real signal, a two-channel-cancellation (TCC) method based on phase compensation is proposed
Guo Rui, Sun Guang-cai, Zhou Feng, Xing Meng-dao   +3 more
openaire   +1 more source

Texture Classification-Based NLM PolSAR Filter

IEEE Geoscience and Remote Sensing Letters, 2021
In this letter, a texture classification-based nonlocal means polarimetric SAR (NLM PolSAR) filter is introduced and named as texture classification-based filter (TBF). In this process, a classification algorithm that identifies the data into textural variations and heterogeneity due to speckle noise is presented.
Rakesh Sharma, Rajib Kumar Panigrahi
openaire   +1 more source

River Ice Mapping from PolSAR Images

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
This paper presents different mapping algorithms to discriminate river ice types using full-polarized C-band and dual-polarized X-band data. Field data are conjointly used with an electromagnetic river ice model to simulate backscattering response of river ice. Finally different classifications, proposed and tested, show encouraging results.
S. Mermoz, S. Allain, M. Bernier, E. Pottier   +3 more
openaire   +1 more source

Superpixel-based PolSAR images change detection

2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), 2015
Previous polarimetric synthetic aperture radar (PolSAR) images change detection methods are generally undertaken in the pixel scale, resulting in overlooking the semantic information. To solve this problem, this paper presents a superpixel-based PolSAR images change detection methods.
Lei Xie, Hong Zhang, Chao Wang, Meng Liu, Bo Zhang   +4 more
openaire   +1 more source

Online Semisupervised Active Classification for Multiview PolSAR Data

IEEE Transactions on Cybernetics, 2022
Polarimetric synthetic aperture radar (PolSAR) data are sequentially acquired and have multiple views obtained from different feature extractors or multiple frequency bands. The fast and accurate classification of PolSAR data in dynamically changing environments is a critical and challenging task.
Xiangli Nie, Mingyu Fan, Xiayuan Huang, Wenjing Yang, Bo Zhang, Xiaoshuang Ma   +5 more
openaire   +2 more sources

An evaluation of PolSAR speckle filters

2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
Speckle suppression in PolSAR images is an important step for the extraction of meaningful information from PolSAR images, especially for homogeneous extended targets. It has been shown that insufficient noise filtering resulting in low equivalent number of look (ENL) values will increase bias on incoherent polarimetric parameters such as the Cloude ...
Samuel Foucher, Carlos Lopez-Martinez
openaire   +1 more source

Analysis of non-Gaussian POLSAR data

2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
In this paper we present a generalised Wishart classifier derived from a non-Gaussian model for polarimetric synthetic aperture radar (POLSAR) data. Our starting point is to demonstrate that the scale mixture of Gaussian (SMoG) distribution model is suitable for modelling POLSAR data.
Anthony Doulgeris, Stian Normann Anfinsen, Torbjorn Eltoft   +2 more
openaire   +1 more source

Assessment of Model-Based Polsar Decompositions

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Model-based polarimetric decompositions are often used to generate scene classifications from polarimetric SAR imagery. The original Freeman-Durden model has been modified and improved upon multiple times over the past 2 decades. However, quantitative, in-depth analyses of these incoherent model-based decompositions have lagged in comparison.
Thomas L. Ainsworth, Jong-Sen Lee, Yanting Wang   +2 more
openaire   +1 more source