基于同质像素预选择的极化SAR图像非局部均值滤波

杨学志; 陈靖; 周芳; 郎文辉; 郑鑫; 李国强

doi:10.11999/JEIT150314

基于同质像素预选择的极化SAR图像非局部均值滤波

doi: 10.11999/JEIT150314

2.
(合肥工业大学计算机与信息学院合肥 230009) ②(光电控制技术重点实验室洛阳 471009)

基金项目:

国家自然科学基金(61371154, 41076120, 61271381, 61102154)，光电控制技术重点实验室和航空科学基金联合资助项目(201301P4007)和中央高校基本科研业务费专项(2012HGCX0001)

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出版历程
- 收稿日期: 2015-03-17
- 修回日期: 2015-08-28
- 刊出日期: 2015-12-19

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

摘要: 该文针对在极化合成孔径雷达(PolSAR)图像相干斑抑制过程中结构特征和极化散射特性保持的难题，提出一种基于同质像素预选择的非局部均值滤波算法(NLM-HPP)。该算法结合像素统计特性和极化散射机制选择滤波同质像素，并引入结构损失函数提高非局部均值(NLM)算法中像素间相似性度量的准确性，最后用改进的相似性度量对同质像素的协方差矩阵进行加权平均，实现对PolSAR图像的相干斑抑制。对真实PolSAR数据进行的实验结果表明，与现有的Refined Lee滤波、基于散射模型的滤波方法和两种非局部均值滤波相比，此方法在有效滤除相干斑点的同时能更好地保持PolSAR图像的结构信息和极化信息。
- 极化合成孔径雷达 /
- 非局部均值 /
- 结构保持 /
- 极化信息 /
- 同质像素预选择
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.
- Polarimetric SAR (PolSAR) /
- Non Local Means (NLM) /
- Structure preserving /
- Polarimetric information /
- Homogeneous pixels preselection

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参考文献(25)

Alonso-Gonzlez A, Lpez-Martnez C, and Salembier P. Filtering and segmentation of polarimetric SAR data based on binary partition trees[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(2): 593-605.

周晓光, 匡纲要, 万建伟. 多极化SAR图像斑点抑制综述[J]. 中国图象图形学报, 2008, 13(3): 377-385.

Zhou Xiao-guang, Kuang Gang-yao, and Wan Jian-wei. A review of polarimetric SAR speckle reduction[J]. Journal of Image and Graphics, 2008, 13(3): 377-385.

Lee J S, Grunes M R, Schuler D L, et al.. Scattering- model-based speckle filtering of polarimetric SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(1): 176-187.

Lee J S, Grunes M R, and De Grandi G. Polarimetric SAR speckle filtering and its implication for classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5): 2363-2373.

Deledalle C A, Denis L, and Tupin F. Iterative weighted maximum likelihood denoising with probabilistic patch-based weights[J]. IEEE Transactions on Image Processing, 2009, 18(12): 2661-2672.

Liu G and Zhong H. Nonlocal means filter for polarimetric SAR data despeckling based on discriminative similarity measure[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(2): 514-518.

Chen J, Chen Y, An W, et al.. Nonlocal filtering for polarimetric SAR data: A pretest approach[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(5): 1744-1754.

Lee J S, Ainsworth T L, Wang Y, et al.. Polarimetric SAR speckle filtering and the extended sigma filter[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(3): 1150-1160.

易子麟, 尹东, 胡安洲, 等. 基于非局部均值滤波的SAR图像去噪[J]. 电子与信息学报,2012, 34(4): 950-955.

Yi Z L, Yin D, Hu A Z, et al.. SAR image despeckling based on non-local means filter[J]. Journal of Electronics and Information Technology, 2012, 34(4): 950-955.

Buades A, Coll B, and Morel J M. A non-local algorithm for image denoising[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, USA, 2005, 2: 60-65.

钟莹, 杨学志, 唐益明, 等. 采用结构自适应块匹配的非局部均值去噪算法[J]. 电子与信息学报, 2013, 35(12): 2908-2915.

Zhong Y, Yang X Z, Tang Y M, et al.. Non-local means denoising derived from structure-adapted block matching[J]. Journal of Electronics Information Technology, 2013, 35(12): 2908-2915.

Torres L, Sant'Anna S J S, da Costa Freitas C, et al.. Speckle reduction in polarimetric SAR imagery with stochastic distances and nonlocal means[J]. Pattern Recognition, 2014, 47(1): 141-157.

Zhong H, Zhang J, and Liu G. Robust polarimetric SAR despeckling based on nonlocal means and distributed Lee filter[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(7): 4198-4210.

Deledalle C A, Tupin F, and Denis L. Polarimetric SAR estimation based on non-local means[C]. IEEE International on Geoscience and Remote Sensing Symposium, Hawaii, USA, 2010: 2515-2518.

D'Hondt O, Guillaso S, and Hellwich O. Iterative bilateral filtering of polarimetric SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(3): 1628-1639.

Deledalle C A, Denis L, Poggi G, et al.. Exploiting patch similarity for SAR image processing: the nonlocal paradigm [J]. IEEE Signal Processing Magazine, 2014, 31(4): 69-78.

Lee J S, Wen J H, Ainsworth T L, et al.. Improved sigma filter for speckle filtering of SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(1): 691-707.

Dellepiane S G and Angiati E. Quality assessment of despeckled SAR images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(2): 691-70.

Hebar M, Gleich D, and Cucej Z. Autobinomial model for SAR image despeckling and information extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(8): 2818-2835.

Ding Z, Zeng T, Dong F, et al.. An improved PolSAR image speckle reduction algorithm based on structural judgment and hybrid four-component polarimetric decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(8): 4438-4449.

Feng H, Hou B, and Gong M. SAR image despeckling based on local homogeneous-region segmentation by using pixel-relativity measurement[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(7): 2724-2737.

Lee J S, Grunes M R, Pottier E, et al.. Unsupervised terrain classification preserving polarimetric scattering characteristics[J]. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(4): 722-731.

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