Statistical modeling of SAR images: A survey
G Gao - Sensors, 2010 - mdpi.com
Statistical modeling is essential to SAR (Synthetic Aperture Radar) image interpretation. It
aims to describe SAR images through statistical methods and reveal the characteristics of …
aims to describe SAR images through statistical methods and reveal the characteristics of …
Deep learning methods for synthetic aperture radar image despeckling: An overview of trends and perspectives
Synthetic aperture radar (SAR) images are affected by a spatially correlated and signal-
dependent noise called speckle, which is very severe and may hinder image exploitation …
dependent noise called speckle, which is very severe and may hinder image exploitation …
Dense attention pyramid networks for multi-scale ship detection in SAR images
Z Cui, Q Li, Z Cao, N Liu - IEEE Transactions on Geoscience …, 2019 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) is an active microwave imaging sensor with the capability of
working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR …
working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR …
Multi-scale ship detection from SAR and optical imagery via a more accurate YOLOv3
Deep learning detection methods use in ship detection remains a challenge, owing to the
small scale of the objects and interference from complex sea surfaces. In addition, existing …
small scale of the objects and interference from complex sea surfaces. In addition, existing …
[HTML][HTML] 复杂场景下单通道SAR 目标检测及鉴别研究进展综述
杜兰， 王兆成， 王燕， 魏迪， 李璐 - 雷达学报, 2020 - radars.ac.cn
SAR 作为一种主动式微波成像传感器, 以其全天时, 全天候, 作用距离远等独特的技术优势,
成为当前对地观测的主要手段之一, 在军事和民用领域发挥着十分重要的作用. 随着SAR …
成为当前对地观测的主要手段之一, 在军事和民用领域发挥着十分重要的作用. 随着SAR …
SAR image segmentation based on convolutional-wavelet neural network and Markov random field
Synthetic aperture radar (SAR) imaging system is usually an observation of the earths'
surface. It means that rich structures exist in SAR images. Convolutional neural network …
surface. It means that rich structures exist in SAR images. Convolutional neural network …
Speckle2Void: Deep self-supervised SAR despeckling with blind-spot convolutional neural networks
Information extraction from synthetic aperture radar (SAR) images is heavily impaired by
speckle noise, and hence, despeckling is a crucial preliminary step in scene analysis …
speckle noise, and hence, despeckling is a crucial preliminary step in scene analysis …
[图书][B] Fading and shadowing in wireless systems
PM Shankar - 2017 - books.google.com
This book offers a comprehensive overview of fading and shadowing in wireless channels. A
number of statistical models including simple, hybrid, compound and cascaded ones are …
number of statistical models including simple, hybrid, compound and cascaded ones are …
Target detection in synthetic aperture radar imagery: A state-of-the-art survey
K El-Darymli, P McGuire, D Power… - Journal of Applied …, 2013 - spiedigitallibrary.org
Target detection is the front-end stage in any automatic target recognition system for
synthetic aperture radar (SAR) imagery (SAR-ATR). The efficacy of the detector directly …
synthetic aperture radar (SAR) imagery (SAR-ATR). The efficacy of the detector directly …
SAR speckle reduction using wavelet denoising and Markov random field modeling
The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery makes
it very difficult to visually and automatically interpret SAR data. Therefore, speckle reduction …
it very difficult to visually and automatically interpret SAR data. Therefore, speckle reduction …