Polarimetric SAR image classification using binary coding‐based polarimetric‐morphological features-Reference-Cited by-同舟云学术

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Polarimetric SAR image classification using binary coding‐based polarimetric‐morphological features

Published:2022-07-14 Issue:14 Volume:16 Page:3715-3736
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Imani Maryam¹^ORCID

Affiliation:

1. Image processing and Information Analysis Lab Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12587

Reference38 articles.

1. Adaptive vectorial total variation models for multi‐channel synthetic aperture radar images despeckling with fast algorithms

2. PolSAR image segmentation based on feature extraction and data compression using Weighted Neighborhood Filter Bank and Hidden Markov random field-expectation maximization

3. A three-component scattering model for polarimetric SAR data

4. Scattering property based contextual PolSAR speckle filter;Mullissa A.G.;Int. J. Appl. Earth Obs. Geoinf.,2017

5. Assessment of the effectiveness of support vector machines for hyperspectral data

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