两种稀疏孔径光学成像的图像恢复算法研究  

Two Algorithms of Images 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,陕西西安710119 [2]中国科学院研究生院,北京100039

出　　处：《光电技术应用》2009年第3期56-58,62,共4页Electro-Optic Technology Application

摘　　要：根据稀疏孔径光学系统成像的图像恢复模型,分析维纳滤波和最小二乘方滤波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,维纳滤波的理论推导能够达到最优.通过实验对比,指出噪声功率谱未知情况,最小二乘方滤波的恢复结果优于维纳滤波结果.According to the model of images restoration for sparse aperture optical systems, the adapted con- ditions to the algorithms of image restoration for the Wiener filtering and the least squares filtering are analyzed. Considering sparse aperture optical systems with noises, the theoretically calculation of Wiener filtering could be optimized. By contrasting with the experiments, it is known that the restoration result of the least squares filter- ing is better than that of the Wiener filtering in the case of having not known the noise power spectrum.

关 键 词：图像处理 最小二乘方滤波 维纳滤波 稀疏孔径 

分 类 号：TN911.74[电子电信—通信与信息系统]