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

机译:基于隐马尔可夫树模型在双树复杂小波域中的海洋石油泄漏SAR图像检测

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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:海洋油溢出SAR图像中相干斑点噪声的存在严重影响了后续图像分割,特征提取和分类。为了更有效地抑制海洋油溢出SAR图像中的斑点噪声,一种基于双树复合小波(DT-CW)的隐马尔可夫树(HMT)模型抑制海洋油溢出SAR图像中散斑噪声的方法本文提出了域名。大量的实验结果表明,与lee滤波器和kuan滤波器等两种经典过滤方法相比,以及基于小波域中的HMT模型的方法,本文提出的方法具有卓越的综合性能,根据主观的视觉和客观定量评估。

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