Abstract
The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, even when the patch size has a small enough setting (e.g., 3 × 3 windows). Therefore, this paper proposes an adaptive nonlocal mean filter with shape-adaptive patches matching (ANLM) for PolSAR images. Mainly, the shape-adaptive (SA) matching patches are constructed by combining the polarimetric likelihood ratio test for coherency matrices (PolLRT-CM) and the region growing (RG), which is called PolLRT-CMRG. It is used to distinguish the homogeneous and heterogeneous pixels in textured areas effectively. Then, to enhance the filtering effect, it is necessary to take the adaptive threshold selection of similarity test (Simi-Test) into consideration. The simulated, low spatial resolution SAR580-Convair and high spatial resolution ESAR PolSAR image datasets are selected for experiments. We make a detailed quantitative and qualitative analysis for the filtered results. The experimental results have demonstrated that the proposed ANLM filter has better performance in speckle suppression and detail preservation than that of the traditional local and nonlocal filters.
Highlights
Polarimetric synthetic aperture radar (PolSAR) can measure the polarimetric characteristic of terrain echo and play an important role in remote sensing field [1]
PolSAR images acquired by airborne and spaceborne sensors can observe abundant terrain features used for many applications, for example, terrain classification [2,3,4], target detection [5,6], disaster monitoring [7,8], topography [9,10] and biomass estimation [11,12], etc
For solving the above two problems, we propose the adaptive nonlocal mean filter (ANLM) filter to improve the performance on homogeneous pixel selection more accurately and robustly
Summary
Polarimetric synthetic aperture radar (PolSAR) can measure the polarimetric characteristic of terrain echo and play an important role in remote sensing field [1]. The application performance of PolSAR images is affected by speckle noise in coherent radar echo imaging systems because speckle noise seriously degrades the image quality [13,14]. Speckle filtering methods of PolSAR images have attracted the attention of many scholars and prompted many investigations in the past several decades. With the purpose of maintaining a good balance between speckle removal and polarimetric characteristic preservation, many effective local or nonlocal speckle filtering methods have been proposed for PolSAR images [13,15,16,17]. The second step has already been studied well, with many methods including average, weighted average [16,18], Lee filter [13,15,19], distributed Lee filter [20] and nonlocal reduced bias estimation (NLRB) [17] being proposed. The weighted average is Sensors 2018, 18, 2215; doi:10.3390/s18072215 www.mdpi.com/journal/sensors
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