Building damage assessment from PolSAR data using texture parameters of statistical model
Author:
Funder
National Natural Science Foundation of China
Publisher
Elsevier BV
Subject
Computers in Earth Sciences,Information Systems
Reference37 articles.
1. Application of the matrix-variate Mellin transform to analysis of polarimetric radar images;Anfinsen;IEEE Trans. Geosci. Rem. Sens.,2011
2. Building-damage detection using post-seismic high-resolution SAR satellite data;Balz;Int. J. Remote Sens.,2010
3. Fisher distribution for texture modeling of polarimetric SAR data;Bombrun;Geosci. Rem. Sens. Lett. IEEE,2008
4. Survey and comparative analysis of entropy and relative entropy thresholding techniques;Chang;IEE Proc. Vis. Image Signal Process.,2007
5. Building collapse extraction using modified freeman decomposition from post-disaster polarimetric SAR image;Chen,2016
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1. A Novel Texture Feature Based on Fourier Transform for Building Damage Recognition from PolSAR Data;Sensors and Materials;2023-11-29
2. Real-time autonomous indoor navigation and vision-based damage assessment of reinforced concrete structures using low-cost nano aerial vehicles;Journal of Building Engineering;2023-06
3. Learning Scattering Similarity and Texture-Based Attention With Convolutional Neural Networks for PolSAR Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2023
4. Improved Swin Transformer-Based Semantic Segmentation of Postearthquake Dense Buildings in Urban Areas Using Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2023
5. Entropy/anisotropy/alpha based 3DGabor filter bank for PolSAR image classification;Geocarto International;2022-11-11
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