SAR图像相干斑抑制中的像素相关性测量

摘要

The Pixel Relativity (PR) measurement of SAR image, which is the key of the despeckling techniques based on weighted average, is researched in three aspects. Firstly, the rationality of ratio PR model is expounded, and two new ratio PR models, which are the LOG-domain Gaussian model and the pixel similarity probability model, are proposed. Meanwhile, the Probability Density Function (PDF) of SAR image and the PDF of the ratio between pixels are transformed into ratio PR models. Then, in order to evaluate the four ratio PR models, the weighted maximum likelihood filters are designed using the PR. Finally, a novel method, performed by calibrating the maximum location of the PR model, is introduced to improve the radiation preservation of those models whose maximum do not locate at 1. The effectiveness of the two proposed PR models and the approach to calibrate the maximum location of the PR model, are indicated by the theoretical analysis and experimental comparison.%　　像素相关性(Pixel Relativity, PR)测量是权重平均相干斑抑制算法中的关键技术,该文从3个方面对SAR图像中的PR模型进行了研究。首先,该文论述了比值PR模型的合理性,提出了两种新的比值PR模型(对数高斯模型与像素相似概率模型),并将SAR图像概率密度函数与比值概率密度函数转化为比值PR模型；然后,为了对4种PR模型应用于相干斑抑制的性能进行比较,设计了基于PR的权重最大似然滤波器；最后,针对相关性最大值位置不为1的PR模型存在的辐射保持能力差的问题,提出了模型最大值位置校正的方法。理论分析与实验表明了提出模型及最大值位置校正方法的有效性。