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基于同質(zhì)像素預選擇的極化SAR圖像非局部均值濾波

楊學志,  陳靖,  周芳,  郎文輝,  鄭鑫,  李國強

楊學志, 陳靖, 周芳, 郎文輝, 鄭鑫, 李國強. 基于同質(zhì)像素預選擇的極化SAR圖像非局部均值濾波[J]. 電子與信息學報, 2015, 37(12): 2991-2999. doi: 10.11999/JEIT150314
引用本文: 楊學志, 陳靖, 周芳, 郎文輝, 鄭鑫, 李國強. 基于同質(zhì)像素預選擇的極化SAR圖像非局部均值濾波[J]. 電子與信息學報, 2015, 37(12): 2991-2999. doi: 10.11999/JEIT150314
Yang Xue-zhi, Chen Jing, Zhou Fang, Lang Wen-hui, Zheng Xin, Li Guo-qiang. Polarimetric SAR Image Despeckling Using Non Local Means Filter Based on Homogeneous Pixels Preselection[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2991-2999. doi: 10.11999/JEIT150314
Citation: Yang Xue-zhi, Chen Jing, Zhou Fang, Lang Wen-hui, Zheng Xin, Li Guo-qiang. Polarimetric SAR Image Despeckling Using Non Local Means Filter Based on Homogeneous Pixels Preselection[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2991-2999. doi: 10.11999/JEIT150314

基于同質(zhì)像素預選擇的極化SAR圖像非局部均值濾波

doi: 10.11999/JEIT150314 cstr: 32379.14.JEIT150314
  • 2.

    (合肥工業(yè)大學計算機與信息學院 合肥 230009) ②(光電控制技術(shù)重點實驗室 洛陽 471009)

基金項目: 

國家自然科學基金(61371154, 41076120, 61271381, 61102154)，光電控制技術(shù)重點實驗室和航空科學基金聯(lián)合資助項目(201301P4007)和中央高校基本科研業(yè)務(wù)費專項(2012HGCX0001)

Polarimetric SAR Image Despeckling Using Non Local Means Filter Based on Homogeneous Pixels Preselection

  • 2.

    (School of Computer and Information, Hefei University of Technology, Hefei 230009, China)

Funds: 

The National Natural Science Foundation of China (61371154, 41076120, 61271381, 61102154)

  • 摘要: 該文針對在極化合成孔徑雷達(PolSAR)圖像相干斑抑制過程中結(jié)構(gòu)特征和極化散射特性保持的難題，提出一種基于同質(zhì)像素預選擇的非局部均值濾波算法(NLM-HPP)。該算法結(jié)合像素統(tǒng)計特性和極化散射機制選擇濾波同質(zhì)像素，并引入結(jié)構(gòu)損失函數(shù)提高非局部均值(NLM)算法中像素間相似性度量的準確性，最后用改進的相似性度量對同質(zhì)像素的協(xié)方差矩陣進行加權(quán)平均，實現(xiàn)對PolSAR圖像的相干斑抑制。對真實PolSAR數(shù)據(jù)進行的實驗結(jié)果表明，與現(xiàn)有的Refined Lee濾波、基于散射模型的濾波方法和兩種非局部均值濾波相比，此方法在有效濾除相干斑點的同時能更好地保持PolSAR圖像的結(jié)構(gòu)信息和極化信息。
    Abstract: A Non Local Means (NLM) filtering based on Homogeneous Pixels Preselection (NLM-HPP) is proposed to solve the problem of preserving structural feature and polarimetric scattering properties in speckle reduction of Polarimetric SAR (PolSAR) images. Firstly, this method combines statistical property and polarimetric scattering mechanism to select homogeneous pixels in the filtering process. Secondly, the loss function of structure is introduced to improve the accuracy of similarity measure between pixels in NLM method. Finally, it averages the covariance matrices of homogeneous pixels with the weights according to the refined similarity measure, inducing efficient reduction of the speckle in PolSAR images. The implementation results on real PolSAR images, compared with the Refined Lee filter, Scattering-Model-Based speckle filter and two kinds of Non Local Means filter, demonstrate that the proposed method can reduce speckle effectively, and further retain structural information and polarimetric information in PolSAR images.
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出版歷程
  • 收稿日期:  2015-03-17
  • 修回日期:  2015-08-28
  • 刊出日期:  2015-12-19

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