激光偏振成像散斑统计特性和抑制方法研究  

Speckle Characteristics of Laser Radar Polarization Imaging and Despecking Algorithm

作　　者：闻东海[1] 江月松[1] 张绪国[1] 张彦仲[1] 华厚强[1] 

机构地区：[1]北京航空航天大学电子信息工程学院,北京100191

出　　处：《光学学报》2013年第3期122-129,共8页Acta Optica Sinica

基　　金：国家自然科学基金(41140035);国家973计划(2011CB707001);国家863计划(2012AA8126029B)资助课题

摘　　要：对激光偏振成像系统的散斑统计特性及其相应的散斑去除方法进行了理论和实验研究。运用穆勒矩阵法建立了该激光偏振成像系统散斑光强的概率分布模型。针对现代电荷耦合器件(CCD)的成像特点,通过比较散斑与像素的大小,将散斑分为两种情况进行研究,即小散斑和大散斑。得出散斑的归一化方差与像素成线性关系,均值不受像素的影响。进而提出了统一的散斑噪声概率模型,即改进的伽马分布模型。基于此模型,提出了改进的贝叶斯非局部滤波模型。通过处理真实的偏振图片,综合等效视数、边缘增强指数等指标,表明该算法比传统的散斑去除算法具有更好的散斑去除和边缘保持能力。The theoretical and the experimental investigations of the laser polarization imaging system of speckle statistical characteristics and speckle removing method are conducted. A probability distribution model for speckle intensity of laser active polarization imaging system by using M/iller matrix is proposed. According to modern charge coupled device （CCD） imaging characteristics, through comparison of speckle and pixel size speckles are divided into two kinds, namely small speckle and big speckle. The normalized variance of speckle is linear to pixel, and the mean value of speckle is irrelevant to pixel. A unified speckle noise probability model, namely the improved Gamma distribution model is proposed. Based on this model, the improved Bayesian nonlocal algorithm is presented. The despeckling results show that equivalent number of looks and edge preserve index outperform those of traditional methods.

关 键 词：统计光学 散斑概率分布模型 穆勒矩阵法 散斑 非局部算法 

分 类 号：O436.3[机械工程—光学工程]