Wake detection: a multichannel approach (SAR image)

1992 ◽  
Author(s):  
J.V. Candy
Keyword(s):  
Sar Image ◽  
Wake Detection

scholarly journals Specific Windows Search for Multi-Ship and Multi-Scale Wake Detection in SAR Images

2021 ◽  
Vol 14 (1) ◽  
pp. 25
Author(s):  
Kaiyang Ding ◽  
Junfeng Yang ◽  
Zhao Wang ◽  
Kai Ni ◽  
Xiaohao Wang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Statistical Features ◽  
Test Results ◽  
Sar Images ◽  
Multi Scale ◽  
Wake Detection ◽  
Aperture Radar

Traditional ship identification systems have difficulty in identifying illegal or broken ships, but the wakes generated by ships can be used as a major feature for identification. However, multi-ship and multi-scale wake detection is also a big challenge. This paper combines the geometric and pixel characteristics of ships and their wakes in Synthetic Aperture Radar (SAR) images and proposes a method for multi-ship and multi-scale wake detection. This method first detects the highlight pixel area in the image and then generates specific windows around the centroid, thereby detecting wakes of different sizes in different areas. In addition, all wake components can be located completely based on wake clustering, the statistical features of wake axis pixels can be used to determine the visible length of the wake. Test results on the Gaofen-3 SAR image show the special potential of the method for wake detection.

Improved Noise Filtering Technique For Wake Detection In SAR Image Under Rough Sea Condition

2021 ◽  
Author(s):  
P Subashini ◽  
P V Hareesh Kumar ◽  
S Lekshmi ◽  
M Krishnaveni ◽  
T T Dhivyaprabha
Keyword(s):  
Noise Filtering ◽  
Sar Image ◽  
Filtering Technique ◽  
Wake Detection ◽  
Rough Sea

Iteration Based Polarimetric SAR Image Classification

PIERS Online ◽  
2007 ◽  
Vol 3 (5) ◽  
pp. 625-628
Author(s):  
Jian Yang ◽  
Xiaoli She ◽  
Tao Xiong
Keyword(s):  
Image Classification ◽  
Sar Image ◽  
Polarimetric Sar

Survey on Fast CFAR Detection Algorithms for SAR Image Targets

2012 ◽  
Vol 38 (12) ◽  
pp. 1885 ◽  
Author(s):  
Ming-Bo ZHAO ◽  
Jun HE ◽  
Qiang FU
Keyword(s):  
Sar Image ◽  
Cfar Detection ◽  
Detection Algorithms

Speckle reduction of SAR image based on morphological Haar wavelet

2013 ◽  
Vol 32 (3) ◽  
pp. 746-748 ◽  
Author(s):  
Min LI ◽  
Zi-you ZHANG ◽  
Lin-ju LU
Keyword(s):  
Haar Wavelet ◽  
Speckle Reduction ◽  
Sar Image

Segmentation of SAR Image using Fuzzy C-Means and Filters

2020 ◽  
Vol 8 (1) ◽  
pp. 84-90
Author(s):  
R. Lalchhanhima ◽  
◽  
Debdatta Kandar ◽  
R. Chawngsangpuii ◽  
Vanlalmuansangi Khenglawt ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
State Of The Art ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Spatial Filters ◽  
Fuzzy C Means ◽  
Automatic Clustering ◽  
Intensity Information

Fuzzy C-Means is an unsupervised clustering algorithm for the automatic clustering of data. Synthetic Aperture Radar Image Segmentation has been a challenging task because of the presence of speckle noise. Therefore the segmentation process can not directly rely on the intensity information alone but must consider several derived features in order to get satisfactory segmentation results. In this paper, it is attempted to use the fuzzy nature of classification for the purpose of unsupervised region segmentation in which FCM is employed. Different features are obtained by filtering of the image by using different spatial filters and are selected for segmentation criteria. The segmentation performance is determined by the accuracy compared with a different state of the art techniques proposed recently.

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