$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

An efficient ship detection method for KOMPSAT-5 synthetic aperture radar imagery based on adaptive filtering approach 원문보기

대한원격탐사학회지 = Korean journal of remote sensing, v.33 no.1, 2017년, pp.89 - 95  

Hwang, JeongIn (Department of Geoinformatics, University of Seoul) ,  Kim, Daeseong (Department of Geoinformatics, University of Seoul) ,  Jung, Hyung-Sup (Department of Geoinformatics, University of Seoul)

Abstract ▼ AI-Helper 아이콘AI-Helper

Ship detection in synthetic aperture radar(SAR)imagery has long been an active research topic and has many applications. In this paper,we propose an efficient method for detecting ships from SAR imagery using filtering. This method exploits ship masking using a median filter that considers maximum s...

주제어

#ship detection   #synthetic aperture radar (SAR)   #NL-means filter   #median filter  

AI 본문요약
AI-Helper 아이콘 AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

  • Five looks, in range and azimuth respectively, were applied to reduce the speckle noise in the SLC image and ground range and azimuth pixel spacing were converted to approximately 10 m. After attaining a SAR intensity image and converting the units of the intensity image to decibel (dB), land masking was then carried out using a simulated SAR intensity image from acquired SRTM DEM in the study area. However, the speckle noise remained in the land masked image.
  • Further study objectives include using the latest DEM for masking land, high quality satellite imagery, and a coherence map which has polarization information. Furthermore, we will analyze using machine learning or deep learning instead of a statistical threshold.
  • In this paper, we propose an efficient, simple method to detect ships from high-resolution KOMPSAT-5 imagery using filtering techniques. The KOMPSAT-5 is a high-resolution X-band SAR satellite, and SAR imagery can be utilized successfully for ship detection.
  • Because ships have much higher intensity values than the surrounding sea, the targets can be easily removed by means of a median filter. The measurement performance of the proposed ship detection method was carried out via visual inspection. There were also false alarms due to reasons such as the side lobe effect, a ghost effect in the SAR image, and land masking errors due to insufficient DEM information.

대상 데이터

  • The study area is in the South Sea of Korea adjacent to Busan. This area includes two main ports, one is Busan Port and the other one is Busan New Port, which is located in Changwon, South Gyeongsang Province.

이론/모형

  • In this paper, we proposed an efficient method to detect ships in KOMPSAT-5 SAR imagery. Our method was implemented using a median filtering approach. Because ships have much higher intensity values than the surrounding sea, the targets can be easily removed by means of a median filter.
본문요약 정보가 도움이 되었나요?

참고문헌 (15)

  1. Armstrong, B., and H. Griffiths, 1991. CFAR detection of fluctuating targets in spatially correlated Kdistributed clutter, Proc. of F Radar Signal Processm IEEE, 138(2): 139-152. 

    상세보기 crossref

  2. Alberola-Lopez, C., J.R. Casar-Corredera, and G. de Miguel-Vela, 1999, Object CFAR detection in gamma-distributed textured-background images, Proc. of Vision, Image and Signal Processing, IEE, 146(3): 130-136. 

    상세보기 crossref

  3. Buades, A., B. Coll, and J.M. Morel, 2005. A non-local algorithm for image denoising, Proc. of 2005 Computer Vision and Pattern Recognition, IEEE Computer Society Conference, San Diego, CA, June 20-26, vol. 2, pp. 60-65. 

  4. Farr, T.G., P.A. Rosen, E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, M. Paller, E. Rodriguez, L. Roth, D. Seal, S. Shaffer, J. Shimada, J. Umland, M. Werner, M. Oskin, D. Burbank, and D. Alsdorf, 2007. The Shuttle Radar Topography Mission, Reviews of Geophysics, 45(2): RG2004. 

    상세보기

  5. Hansen, V., 1973. Constant false alarm rate processing in search radars, Proc. of the Radar Present Future, London, October 23-25, pp. 325-332. 

  6. Howard, D., S. Roberts, and R. Brankin, 1999. Target detection in SAR imagery by genetic programming, Advances in Engineering Software, 30(5): 303-311. 

    상세보기 crossref

  7. Kaplan, L.M., 2001. Improved SAR target detection via extended fractal features, IEEE Transactions on Aerospace and Electronic Systems, 37(2): 436-451. 

    상세보기 crossref

  8. Khesali, E., H. Enayatu, M. Modiri, and M.M Aref, 2015. Automatic ship detection in single-Pol-SAR Image using texture features in artificial neural networks, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Science, 40(1): 395-399. 

  9. Ouchi, K., S. Tamaki, H. Yaguchi, and M. Iehara, 2004. Ship detection based on coherence images derived from cross correlation of multilook SAR images, IEEE Geoscience and Remote Sensing Letters, 1(3): 184-187. 

    상세보기 crossref

  10. Rohling, H., 1983. Radar CFAR thresholding in clutter and multiple target situations, IEEE Transactions on Aerospace and Electronic Systems, 19(4): 608-621. 

  11. Souyris, J. C., C. Henry, and F. Adragna, 2003. On the use of complex SAR image spectral analysis for target detection: Assessment of polarimetry, IEEE Transactions on Geoscience and Remote Sensing, 41(12): 2725-2734. 

    상세보기 crossref

  12. Van Zyl, J. J., 2001. The Shuttle Radar Topography Mission (SRTM): a breakthrough in remote sensing of topography, Acta Astronautica, 48(5-12): 559-565. 

    상세보기 crossref

  13. Werner, M., 2001. Shuttle radar topography mission (SRTM) mission overview, Frequenz, 55(3-4): 75-79. 

  14. Wang, X., and C. Chen, 2016. Adaptive ship detection in SAR images using variance WIE-based method, Signal, Image and Video Processing, 10(7): 1219-1224. 

    상세보기 crossref

  15. Wang, C., M. Liao, and X. Li, 2008. Ship detection in SAR image based on the alpha-stable distribution. Sensors, 8(8): 4948-4960. 

    상세보기 crossref

관련 콘텐츠

오픈액세스(OA) 유형

GOLD

오픈액세스 학술지에 출판된 논문

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로