【24h】

Enhanced Ship Detection from Overhead Imagery

机译:从顶上图像提高船舶检测

获取原文

摘要

In the authors' previous work, a sequence of image-processing algorithms was developed that was suitable for detecting and classifying ships from panchromatic Quickbird electro-optical satellite imagery. Presented in this paper are several new algorithms, which improve the performance and enhance the capabilities of the ship detection software, as well as an overview on how land masking is performed.Specifically, this paper describes the new algorithms for enhanced detection including for the reduction of false detects such as glint and clouds. Improved cloud detection and filtering algorithms are described as well as several texture classification algorithms are used to characterize the background statistics of the ocean texture. These detection algorithms employ both cloud and glint removal techniques, which we describe. Results comparing ship detection with and without these false detect reduction algorithms are provided. These are components of a larger effort to develop a low-cost solution for detecting the presence of ships from readily-available overhead commercial imagery and comparing this information against various open-source ship-registry databases to categorize contacts for follow-on analysis.
机译:在作者以前的工作中,图像处理算法的序列被开发,这是适合于检测和分类从全色快鸟电光卫星图像船舶。本文提出了几个新的算法,提高了性能,提高船舶检测软件的能力,以及对土地掩蔽是如何performed.Specifically的概述,本文介绍了新的算法包括降低增强的检测虚假检测,如闪烁和云彩。改进的云检测和过滤算法被描述以及几个纹理分类算法被用于表征海洋纹理的背景的统计信息。这些检测算法采用云和闪光去除技术,这是我们形容。结果船检测比较使用和不使用这些假检测被提供减少的算法。这是一个更大的努力来开发用于探测船从容易获得的开销商业影像的存在和对各种开源船舶登记数据库信息进行比较归类为接触后续的分析低成本解决方案的组成部分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号