稀疏孔径光学系统成像恢复算法研究

Research on Image Restoration for Sparse Aperture Systems

分析了传统小波阈值去噪方法,给出改进去噪算法.先对稀疏孔径光学系统含噪成像,通过改进小波阈值去噪,提高信噪比,最大程度得到较为理想成像结果,参考修正维纳滤波方法,对去噪结果经过修正维纳滤波实现成像恢复.在实验中,考虑结构非冗余性,利用光学设计软件ZEMAX设计Golay6结构不同填充因子的稀疏孔径光学系统,以本算法进行成像恢复.实验结果表明本文算法优于单独使用维纳滤波或修正维纳滤波方法.

The improved algorithm for removing the image noises is presented after analyzing tradition wavelet threshold methods. After the noises being removed from the disturbed images with improved wavelet threshold algorithm, relatively idea images can be received. Then image restoration is realized after improved wiener filtering which has been used for reference. During experiment, Golay6 sparse aperture systems with different fill factors are designed with the aid of the optical design program ZEMAX considering the redundancy of this configuration. It demonstrates that the proposed algorithm is superior to normal or improved Wiener filtering method.