基于小波阈值法和维纳滤波的稀疏孔径光学系统成像的恢复

Imaging restoration for sparse aperture optical systems based on wavelet threshold and Wiener filtering

  • 摘要: 在研究稀疏孔径理想衍射成像光学系统的基础上,提出基于改进小波阈值法和维纳滤波的稀疏孔径光学系统成像恢复算法。针对存在噪声干扰的稀疏孔径光学成像系统,设计并利用改进的小波阈值去噪算法,较好地去除了成像噪声,最大程度地得到较为理想的成像结果,然后利用维纳滤波方法实现成像恢复。在实验中,利用光学设计软件ZEMAX设计了不同填充因子的稀疏孔径光学系统,并用本算法进行了成像恢复。实验结果表明,该算法的结果优于单独使用维纳滤波方法所获得的结果。

     

    Abstract: On the basis of the research on an ideal diffraction optical imaging system with sparse apertures, the algorithm of the imaging restoration for sparse aperture optical systems is proposed based on the improved wavelet threshold method and Wiener filtering. The improved wavelet threshold noiseblanking algorithm was designed to eliminate the imaging noise and obtain the ideal imaging result for the sparse aperture optical imaging systems in which noise jamming exists. And the imaging restoration was realized by using the Wiener filtering method. In the experiment, the optical design software ZEMAX was used to design the sparse aperture optical systems with different fill factors, and the algorithm proposed in this paper was applied to image restoration. The experimental results indicate that the algorithm is superior to the method which uses Wiener filtering only.

     

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