Results 81 to 90 of about 5,464 (214)
Remote SensingSupervised polarimetric synthetic aperture radar (PolSAR) image classification demands a large amount of precisely labeled data. However, such data are difficult to obtain.
Lei Wang +4 more
doaj +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
Artificial Intelligence applications in Noise Radar Technology
IET Radar, Sonar &Navigation, Volume 18, Issue 7, Page 986-1001, July 2024.Abstract Radar systems are a topic of great interest, especially due to their extensive range of applications and ability to operate in all weather conditions. Modern radars have high requirements such as its resolution, accuracy and robustness, depending on the application.
Afonso L. Sénica +2 more
wiley +1 more source
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 +3 more
doaj +1 more source
Polarimetric Incoherent Target Decomposition by Means of Independent Component Analysis [PDF]
, 2015 International audienceThis paper presents an alternative approach for polarimetric incoherent target decomposition dedicated to the analysis of very-high resolution POLSAR images.
Besic, Nikola +3 more
core +3 more sources
IET Radar, Sonar &Navigation, Volume 18, Issue 7, Page 1106-1115, July 2024.The manuscript mainly investigates the sparse distributed vegetation height inversion problem. By analysing the scattering mechanisms of the sparse distributed vegetation, the authors proposed a method to select the samples to estimate PolInSAR coherence and vegetation height in non‐local areas by using the amplitude‐normalised interferometric phase ...
Jing Xu +3 more
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 SensingPolarimetric 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 +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
Earth and Space Science, Volume 11, Issue 4, April 2024.Abstract Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post‐event assessment, offering fire agencies opportunities for additional surveillance with radar, an all‐weather instrument that can image day or night.
Karen An, Cathleen E. Jones, Yunling Lou
wiley +1 more source
Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification
Remote SensingSuperpixel 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 +7 more
doaj +1 more source