稀疏孔径光学系统成像的图像恢复算法研究  

Research on the Image Restoration for Sparse Aperture Optical Systems

作　　者：李波[1,2] 李艳[1] 李昕[1,2] 

机构地区：[1]中国科学院西安光学精密机械研究所,西安710119 [2]中国科学院研究生院,北京100049

出　　处：《光子学报》2010年第2期275-278,共4页Acta Photonica Sinica

摘　　要：提出两种稀疏孔径光学系统成像的图像恢复模型.分析维纳滤波、最小二乘方滤波和极大似然法盲去卷积三种图像恢复算法的适用条件.针对存在噪声干扰的稀疏孔径光学系统,通过实验对比,指出维纳滤波和最小二乘方滤波把相机光学传函当作系统传函,其理论推导能够达到最优.盲去卷积把大气传输函数和相机光学传函作为系统传函进行恢复,其恢复结果优于维纳滤波带入常数K和最小二乘方滤波调整参量结果.Two models of the image restoration for sparse aperture optical systems are proposed. The adapted condition is analysed about Wiener filtering,least squares filtering and MLE blind deconvolution. According to the experiment, the issue points out Wiener filtering and least squares filtering use camara tens＇ OTF as the whole system MTF. In theory the Wiener filtering can make the best image restoration. Considering sparse aperture optical systems with noises, the blind deconvolution uses the atmosphere transfer function and the lens＇ OTF as the system MTF to have a image restoration. The result is better than Wiener filtering using constant K and least squares filtering.

关 键 词：图像处理 维纳滤波 盲去卷积 稀疏孔径 

分 类 号：TN911.73[电子电信—通信与信息系统]