STUDENT MEMBER, IEEE, Remote Sensing Laboratory, Center for Research, Inc., University of Kansas, Lawrence, KS 66045.
IEEE Trans Pattern Anal Mach Intell. 1982 Feb;4(2):157-66. doi: 10.1109/tpami.1982.4767223.
Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.
由于雷达成象过程的相干性,用于增强非相干光产生图象的标准图象处理技术不适用于雷达图象。本文导出了一个雷达成象过程的模型,并提出了一种用于平滑噪声雷达图象的方法。该成象模型表明,雷达图象受到乘性噪声的干扰。该模型导致了用于平滑雷达图象的最优(最小均方误差)滤波器的函数形式。通过使用局部估计的参数值,使滤波器具有自适应性,以便在图象的均匀区域内提供最小均方误差估计,同时保持边缘结构。结果表明,该滤波器可以很容易地在空间域中实现,并且计算效率高。利用实际和模拟雷达图象,对自适应滤波器的性能(定性和定量)与几种标准滤波器进行了比较。