首页    期刊浏览 2024年09月29日 星期日
登录注册

文章基本信息

  • 标题:Automatic Thresholding Techniques for SAR Images
  • 本地全文:下载
  • 作者:Moumena Al-Bayati ; Ali El-Zaart
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2013
  • 卷号:3
  • 期号:3
  • 页码:75-84
  • DOI:10.5121/csit.2013.3308
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Segmentation of Synthetic Aperture Radar (SAR) images have a great use in observing the global environment, and in analysing the target detection and recognition .B ut , segmentation of (SAR) images is known as a very complex task, due to the existence of speckle noise. Therefore, in this paper we present a fast SAR images segmentation based on between class variance. Our choice for used (BCV) method, because it is one of the most effective thresholding techniques for most real world images with regard to uniformity and shape measures. Our experiments will be as a test to determine which technique is effective in thresholding (extraction) the oil spill for numerous SAR images, and in the future these thresholding techniques can be very useful in detection objects in other SAR images.
  • 关键词:SAR;I;MAGES;S;EGMENTATION;T;HRESHOLDING;O;TSU METHOD
国家哲学社会科学文献中心版权所有