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Polarimetric radar image despeckling by using similar patches matching and minimum mean square error filter

  • role： First author第一作者
  • Affiliation：

    School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China

  • Email：mxs.88@163.com
  • Introduction：马晓双，1988年生，男，讲师，研究方向为极化雷达遥感影像处理与解译。E-mail： mxs.88@163.com
Xiaoshuang MA1,  
  • Affiliation：

    School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China

Penghai WU1,  
  • Affiliation：

    Data and Application Center of High-resolution Earth Observation System of Anhui Province, Hefei 230000, China

Shiyu LIU2,  
  • Affiliation：

    Data and Application Center of High-resolution Earth Observation System of Anhui Province, Hefei 230000, China

Mengyuan YAO2

résumé

Synthetic Aperture Radar (SAR) systems are capable of capturing images of the earth in day and night and for almost all weather conditions. Polarimetric SAR (PolSAR), which focuses on emitting and receiving complete polarized radar waves to characterize observed targets, is an advanced form of SAR. PolSAR data have unique advantages in obtaining land cover information in comparison with optical remote sensing data, thereby resulting in their wide use in many areas. However, the SAR data are inherently affected by speckle noise. The presence of speckles complicates the PolSAR image interpretation and land surface parameter inversion. Therefore, despeckling is an essential procedure in most cases before using SAR images to obtain land cover information. In the traditional methods based on the linear minimum mean square error (LMMSE) filter, a group of homogeneous image pixels is first selected in a local window to obtain precise filter parameters in the LMMSE estimator. The LMMSE estimator is then generated from the values of the selected pixels and is saved as the filtered value of the pixel being processed. These methods assume that all of the selected pixels are absolutely homogeneous pixels with respect to the processed pixel, which is insufficiently reliable. In addition, most of these methods have limitations, such as a limited selection range of pixels, which are only compared with the characteristics of their own, thereby possibly producing a biased or inferior estimation of the filter parameters in the estimator. In this study, we proposed a similar patch matching and LMMSE filter combined with a PolSAR despeckling method based on the 3D block matching-based algorithm. The main idea behind the proposed method is to select additional similar pixels in the nonlocal area to improve the performance of the LMMSE estimator. The main process of the proposed method is as follows: first, the similar patches in a nonlocal window for each target patch are selected to form a patch group, and the LMMSE filter is used to filter all the pixels in the group. Second, an aggregation step is utilized to estimate the pixels that have been clustered into several groups. The patch matching process is used again to group similar patches by considering the information of the original and basic estimated images. Finally, a collaborated LMMSE filter and an aggregation step are undertaken to filter the image. The experiments on the simulated PolSAR and two real PolSAR images acquired by the GF-3 satellite revealed the positive despeckling performances of the proposed method. The speckle is reduced to a large degree, and the image details, such as the edges and strong point targets, are effectively preserved.

mots-clés

polarimetric synthetic aperture radar;speckle filtering;similar patches matching;linear minimum mean square error filter;nonlocal means

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