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艾加秋, 王非凡, 杨兴明, 等. 基于背景匀质性双边滤波的SAR图像斑点噪声抑制算法[J]. 遥感学报, 2021,25(5):1071-1084.
Jiaqiu AI, Feifan WANG, Xingming YANG, et al. SAR image speckle noise suppression algorithm based on background homogeneity and bilateral filtering[J]. National Remote Sensing Bulletin, 2021,25(5):1071-1084.
针对双边滤波在抑制SAR图像相干斑噪声的不足，本文提出了一种基于背景匀质性的改进双边滤波算法BH-IBF（Improved Bilateral Filtering algorithm based on Background Homogeneity ），并将其应用于SAR图像斑点噪声抑制。BH-IBF以传统双边滤波作为基本框架，并利用了双边滤波器中的双边核函数描述像素灰度值之间的相似性以及相邻像素间的几何空间信息。然而，传统双边滤波存在不能有效地滤除强斑点噪声的缺点，并且SAR图像又因成像原理的缺陷导致强斑点噪声普遍存在。针对这些问题，BH-IBF设计了一种根据背景窗口的匀质性进行自适应样本截断的方法，并根据描述背景匀质性的指标自动获取样本截断的截断深度。此外，本文将自适应滤波窗口尺寸以及权重核修改的方案应用到BH-IBF中，以增强匀质区域的斑点噪声平滑强度以及异质区域的边缘信息效果。最后，使用自适应截断后的样本作为已调整权重核的双边滤波器的输入。实验数据显示，BH-IBF能够在有效保留SAR图像纹理信息的同时，获取较好的斑点噪声平滑性能。
As a kind of high-resolution imaging radar, Synthetic Aperture Radar (SAR) plays an important role in civil and military fields because it can realize all-weather and all-weather observation without the limitation of illumination and climate conditions. However, SAR also has limitations. For instance, the SAR image has many speckle noises, which is caused by the principle of coherent imaging that seriously affects the extraction and application of relevant information in the image. Therefore, to make better use of SAR image information, speckle noise reduction is a key step in SAR image processing. Among them, the bilateral filtering algorithm, which combines the geometric domain and the gray-scale domain information filter, is currently the best algorithm in the field of speckle noise removal. In this study, we take the bilateral filtering algorithm as the basic framework and then add corresponding improvement measures in view of the problems and shortcomings of the bilateral filtering algorithm, such as insufficient application of SAR image structure information and difficulty in effectively filtering out strong speckle noise. Finally, we propose an improved bilateral filtering algorithm based on background homogeneity (BH-IBF).,This algorithm aims to effectively remove the speckle noise in the SAR image while retaining the real texture information of the image to the maximum extent. (1) The coefficient of variation is introduced into the weight kernel improvement of the bilateral filtering algorithm, compensating for the problem of the bilateral filter ignoring the structural information of the SAR image to a certain extent; (2) the sample truncation operation is introduced to filter the strong speckle noise in the background area to a certain extent, suppressing the influence of speckle noise, thus effectively solving the bilateral filtering. Strong speckle noise is difficult to filter out; (3) the half width of the background region for the homogeneous region can further improve the smoothness of the image.Taking the simulated and real SAR images intercepted from TerraSAR-X as the experimental objects, the comparison of the filtering effects and evaluation indexes of different filtering algorithms shows the improved results obtained by BH-IBF algorithm, indicating that the proposed algorithm achieves the research objective.,The proposed BH-IBF has a better effect than the traditional filtering algorithm. BH-IBF can not only effectively suppress the speckle noise in the homogeneous region but also protect the edge texture information of the heterogeneous region better, that is, the algorithm can better guarantee the subsequent processing and application of SAR data.
SAR图像斑点噪声抑制改进双边滤波算法自适应样本截断背景匀质性自适应滤波窗口尺寸
SAR image speckle noise reductionimprove bilateral filteringadaptive sample trimminghomogeneity index of the reference windowadaptive window size
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