首页> 外文会议>International conference on opto-electronics engineering and information science >Marine Oil Spill SAR Images Despeckling Based on Hidden Markov Tree Model in the Dual-tree Complex Wavelet Domain
【24h】

Marine Oil Spill SAR Images Despeckling Based on Hidden Markov Tree Model in the Dual-tree Complex Wavelet Domain

机译:双树复小波域中基于隐马尔可夫树模型的海上溢油SAR图像去斑

获取原文

摘要

The presence of coherent speckle noise in the marine oil spill SAR images seriously affects the follow-up image segmentation,feature extraction and classification. To suppress more effectively the speckle noise in the marine oil spill SAR images,a method of suppressing the speckle noise in the marine oil spill SAR images based on the hidden Markov tree (HMT) model in dual-tree complex wavelet (DT-CW) domain is proposed in this paper. A large number of experimental results show that,compared with two classical filtering methods such as Lee filter and Kuan filter,and the method based on the HMT model in wavelet domain, the proposed method in this paper has superior comprehensive performance according to subjective visual and objective quantitative evaluation.
机译:海洋溢油SAR图像中存在相干斑点噪声严重影响了后续图像的分割,特征提取和分类。为了更有效地抑制海洋溢油SAR图像中的斑点噪声,基于双树复小波(DT-CW)的基于隐马尔可夫树(HMT)模型的海洋溢油SAR图像中的斑点噪声抑制方法本文提出了一个领域。大量的实验结果表明,与Lee滤波器和Kuan滤波器这两种经典的滤波方法以及基于小波域HMT模型的方法相比,本文提出的方法在主观视觉和视觉上都具有优越的综合性能。客观的定量评估。

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