Image inversion and quality enhancement for space large aperture diffractive imaging system

Kai QIAO; Xi-yang ZHI; Shi-kai JIANG; Lei ZHANG; Zhong-ke YIN

doi:10.3788/OPE.20192707.1465

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Image inversion and quality enhancement for space large aperture diffractive imaging system

Modern Applied Optics | 更新时间：2020-08-13

- Image inversion and quality enhancement for space large aperture diffractive imaging system
- Optics and Precision Engineering Vol. 27, Issue 7, Pages: 1465-1472(2019)
- 作者机构：
  
  1.北京跟踪与通信技术研究所, 北京100094
  2.哈尔滨工业大学空间光学工程研究中心, 黑龙江哈尔滨 150001
  3.北京遥感信息研究所, 北京 100192
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20192707.1465
  CLC： O434.1;TP391.41
- Received：20 December 2018，
  
  Accepted：15 January 2019，
  
  Published：15 July 2019
- 稿件说明：
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Kai QIAO, Xi-yang ZHI, Shi-kai JIANG, et al. Image inversion and quality enhancement for space large aperture diffractive imaging system[J]. Optics and precision engineering, 2019, 27(7): 1465-1472.
DOI：

Kai QIAO, Xi-yang ZHI, Shi-kai JIANG, et al. Image inversion and quality enhancement for space large aperture diffractive imaging system[J]. Optics and precision engineering, 2019, 27(7): 1465-1472. DOI： 10.3788/OPE.20192707.1465.

摘要

面向高轨监视领域对超大口径、轻量化的高分辨率光学载荷的迫切需求

提出了一种以衍射元件为主镜的空间大口径衍射成像系统图像反演恢复与增强方法。针对大口径光学系统像差和主镜衍射效应引起的模糊严重以及点扩散函数空间变化性大等降质问题

基于正则化理论框架和等晕区分块思想

提出了基于多正则化约束的衍射成像系统图像反演恢复方法

研究了多参量多约束模型的高效求解方法。针对衍射效率不足和非设计级次背景杂波引起的图像信噪比低和对比度下降严重的问题

结合小波阈值滤波与非线性变换

提出了自适应的衍射成像系统图像质量增强方法。最后进行了实验验证

实验结果表明:当空变等级达到了3.0时

恢复结果与原始图像的结构相似度在0.8以上

信噪比提升10%以上

信息保真度在80%以上。该方法在有效提升图像清晰度与对比度的同时

提高了图像的信噪比

对超大口径薄膜衍射成像系统的实际空间应用具有一定的理论研究意义和工程应用价值。

Abstract

To address the urgent need for ultra-large aperture and lightweight high-resolution optical payloads in the field of high-orbit military monitoring

an image inversion and quality enhancement method was proposed for large-caliber diffractive imaging systems with diffractive optical elements used as the primary mirror. First

an image inversion model was established for the diffraction imaging system based on the regularization and iso-halo block theories. Here

the multi-regularization and multi-constraint algorithm was adopted for theoretical model optimization

and two bottleneck problems were in turn solved to a certain extent. One was the image blurring caused by both the large-caliber optical system aberration and the diffraction effect of the main mirror; the other was the large spatial variation of the point spread function. Nonlinear transformation and wavelet threshold filtering were then used to formulate a contrast enhancement method to address the low signal-to-noise ratio and low contrast problems that derive from low diffraction efficiency and non-design level sub-background clutter. Finally

experiments and a simulation were conducted to test the proposed method. Experimental results show that the structural similarity of degraded and original images exceeds 0.8

the Signal to Noise Ratio(SNR) is increased by 10% and fidelity is more than 80% with CLE of 3.0. The proposed method improves image quality

including image clarity and contrast as well as the suppression of noise and background radiation. The proposed method thus has great theoretical significance and engineering application value for the practical application of ultra-large aperture thin-film diffraction systems.

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references

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