NDLI: 2D comb feature for analysis of ship classification in high-resolution SAR imagery

Content Provider	IET Digital Library
Author	Leng, Xiangguang Ji, Kefeng Zhou, Shilin Xing, Xiangwei Zou, Huanxin
Abstract	A new feature named ‘2D comb’ to improve ship classification is proposed. The proposed feature presents added value to distinguish between container ship, tank ship and cargo ship. It is based on radar cross-section (RCS) statistic of the ship target related to the ship structure. Besides, related local RCS is proposed to classify three kinds of ships. Experimental results based on TerraSAR-X images show that the proposed feature can abstract and describe the ship structure in high-resolution synthetic aperture radar (SAR) imagery. It establishes relationship between RCS and ship structure, which is very useful to distinguish different kinds of ships.
Starting Page	500
Ending Page	502
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 7, Mar (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.4598
Journal	Electronics Letters
Publisher Date	2017-03-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Comb Feature Cargo Ship Container Ship High-resolution SAR Imagery High-resolution Synthetic Aperture Radar Imagery Image Classification Image Recognition Image Resolution Local RCS Radar Cross-section Statistic Radar Equipment Radar Imaging RCS Statistic Ship Classification Ship Classification Analysis Ships Synthetic Aperture Radar System And Application Tank Ship TerraSAR-X Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Ship signatures in synthetic aperture radar imagery

Classification of high resolution TerraSAR-X Ship chips based on destribution characteristic matrix of scattering centers

Ship recognition in high resolution SAR imagery based on feature selection

A vessel structure feature recognition method based on high resolution TerraSAR-X image

Fast ship contour extraction in SAR images

A one-class-extraction framework for high resolution SAR image classification

Maritime targets classification based on CNN using Gaofen-3 SAR images

Identification and characterization of railway trains in high resolution TerraSAR-X images

Ship detection and recognition combing one-dimensional range profile with SAR image

2D comb feature for analysis of ship classification in high-resolution SAR imagery

Similar Documents

Ship signatures in synthetic aperture radar imagery

Classification of high resolution TerraSAR-X Ship chips based on destribution characteristic matrix of scattering centers

Ship recognition in high resolution SAR imagery based on feature selection

A vessel structure feature recognition method based on high resolution TerraSAR-X image

Fast ship contour extraction in SAR images

A one-class-extraction framework for high resolution SAR image classification

Maritime targets classification based on CNN using Gaofen-3 SAR images

Identification and characterization of railway trains in high resolution TerraSAR-X images

Ship detection and recognition combing one-dimensional range profile with SAR image

2D comb feature for analysis of ship classification in high-resolution SAR imagery