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An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3. [PDF]
Liu W, Yang J, Zhao J, Shi H, Yang L.
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Research progress on multimodal data fusion in forest resource monitoring. [PDF]
Wang M +6 more
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Gaofen-3 PolSAR Image Classification via XGBoost and Polarimetric Spatial Information. [PDF]
Dong H, Xu X, Wang L, Pu F.
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Survey on Context-Aware Radio Frequency-Based Sensing. [PDF]
Casmin E, Oliveira R.
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A Mobile Analytical Chemistry Workstation with a C4D Sensor for Rapid Detection of Organophosphates Under Field Conditions. [PDF]
Wang Y +5 more
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Marine Oil Pollution Monitoring Based on a Morphological Attention U-Net Using SAR Images. [PDF]
Chang L +4 more
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ICA based PolSAR image denoising
2016 12th IEEE International Symposium on Electronics and Telecommunications (ISETC), 2016A 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 +4 more
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Jamming suppression in Dual-channel PolSAR
2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar, 2009In 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 +3 more
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Texture Classification-Based NLM PolSAR Filter
IEEE Geoscience and Remote Sensing Letters, 2021In 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
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