Generation of non-Rayleigh speckle distributions using marked regularity models
Generation of non-Rayleigh speckle distributions using marked regularity models
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DOI：
10.1109/58.775652
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发表时间：
1999-07-01
影响因子：
3.6
通讯作者：
Parker, KJ
中科院分区：
文献类型：
--
作者：
Cramblitt, RM;Parker, KJ
在相干图像中观察到的完全发育的散斑图案的特征是瑞利分布的包络幅度。在许多情况下都会观察到非瑞利分布，例如当分辨率单元中的散射体数量较小或散射体以某种周期性组织时。由随机散射体相位假设（随机游走模型）产生的分布已用于描述这些情况下的散斑幅度，从而产生 K、莱斯和零差 K 幅度分布。另一种方法是通过采用直接描述点散射体空间放置的模型来隐式合并非随机相位。我们研究了假设散射是通过平稳更新过程在一维中描述的结果，其中到达时间是理想点散射体的位置，散射体间距离是从伽马分布中得出的，并且允许散射体振幅在空间中相关。该模型被称为标记规律性模型，因为模型参数的变化可以生成从聚集到随机再到近周期性的空间分布。我们将证明，由先前的随机相位模型生成的所有非瑞利分布也可以由标记正则性模型生成，并且我们将展示在什么条件下会产生不同的分布。我们还证明了正则性模型本质上能够描述某些稀疏散射条件。因此，该模型可以代表许多情况，并对散射体的空间放置提供直观、令人愉悦的描述。
Fully developed speckle patterns observed in coherent imagery are characterized by a Rayleigh-distributed envelope amplitude. Non-Rayleigh distributions are observed in many cases, such as when the number of scatterers in a resolution cell is small or scatterers are organized with some periodicity. Distributions resulting from the assumption of random scatterer phase (random walk models) have been used to describe the speckle amplitude in these cases, leading to K, Rician, and homodyned-K amplitude distributions. An alternative is to incorporate non random phase implicitly by adopting models that directly describe the spatial placement of point scatterers. We examine the consequences of assuming that scattering is described in one dimension by a stationary renewal process in which the arrival times are the locations of ideal point scatterers, the interscatterer distances are drawn from a gamma distribution, and the scatterer amplitudes are allowed to be correlated in space. This model has been called the marked regularity model because variations of the model parameters can generate spatial distributions ranging from clustered to random to nearly periodic. We will demonstrate that all of the non-Rayleigh distributions generated by the previous random phase models can also be generated by the marked regularity model, and we show under what conditions the different distributions will result. We also demonstrate that the regularity model is inherently capable of describing certain sparse scattering conditions. Therefore, the model can represent many cases and provide an intuitively pleasing description of the spatial placement of the scatterers.