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1.中国科学院上海技术物理研究所,上海 200083
2.中国科学院大学,北京 100049
3.中国科学院红外探测与成像技术实验室,上海 200083
[ "马一哲(1997-),男,陕西西安人,博士研究生,2019年于西安工程大学获得学士学位,现为中国科学院上海技术物理研究所研究生,主要从事红外偏振成像系统技术,数字图像信号处理,图像超分辨方面的研究。E-mail: mayizhe@mail.sitp.ac.cn" ]
[ "李范鸣(1969-),男,江苏省人,研究员,博士生导师,1992年于上海科学技术大学获得学士学位,1999年于中国科学院获得硕士学位,2007年于中国科学院获得博士学位,现任中国科学院上海技术物理研究所五室主任,主要从事红外系统工程、红外成像技术、多维信息获取及微弱目标探测技术方面的研究工作。E-mail: lfmjws@163.com" ]
收稿日期:2023-02-13,
修回日期:2023-03-13,
纸质出版日期:2023-08-25
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马一哲,王世勇,雷腾等.分焦平面红外偏振微扫描图像超分辨重建[J].光学精密工程,2023,31(16):2418-2429.
MA Yizhe,WANG Shiyong,LEI Teng,et al.Superresolution reconstruction of infrared polarization microscan images in focal plane[J].Optics and Precision Engineering,2023,31(16):2418-2429.
马一哲,王世勇,雷腾等.分焦平面红外偏振微扫描图像超分辨重建[J].光学精密工程,2023,31(16):2418-2429. DOI: 10.37188/OPE.20233116.2418.
MA Yizhe,WANG Shiyong,LEI Teng,et al.Superresolution reconstruction of infrared polarization microscan images in focal plane[J].Optics and Precision Engineering,2023,31(16):2418-2429. DOI: 10.37188/OPE.20233116.2418.
分焦平面偏振探测系统受其探测器结构的影响,成像分辨率低于探测器实际分辨率,本文在不改变光学系统结构下使用微扫描获取亚像元微位移帧序列,提出一种改进的凸集投影(Projection On Convex Sets
POCS)算法用于提升偏振成像系统的成像分辨率。该算法首先对获取到的偏振微扫描图像序列进行检偏角分离,将同组检偏角图像序列作为输入,其次进行位移匹配与凸集投影迭代初步重建高分辨率图像,然后将图像分组进行滑动窗口非邻域聚类,利用主成分分析将聚类后的图像进行降维,最后将每一维信息视为时间采样函数,在小波域进行软阈值降噪。实验表明,本算法可以有效的提高传统POCS算法的抗噪性能,提高分焦平面偏振探测系统的成像分辨率,和同类算法相比结构相似性系数提升0.02,峰值信噪比提升约1 dB,并且拥有更高的噪声鲁棒性。
The imaging resolution of a polarization detection system in the focal plane is lower than the actual resolution of the detector owing to the influence of the detector structure. In this study, micro-scanning is used to obtain the micro-displacement frame sequence without changing the optical system structure, and an improved convex set projection (POCS) algorithm is proposed to improve the imaging resolution of the polarization imaging system. In the algorithm, the obtained polarization microscan image sequences were first separated through angle detection, and the same group of angle detection image sequences were used as the input. Second, displacement matching and convex set projection iteration were conducted to initially reconstruct high-resolution images. Thereafter, the images were grouped into sliding window non-neighborhood clustering, and the dimensionality of the clustered images was reduced through principal component analysis. Finally, each one-dimensional information was regarded as a time sampling function, and soft threshold denoising was conducted in the wavelet domain. Experiments demonstrate that this algorithm can effectively improve the anti-noise performance of the conventional POCS algorithm, improve the imaging resolution of the high-resolution focal plane polarization detection system, increase the structural similarity coefficient by 0.02, increase the peak signal-to-noise ratio by 1 dB compared with similar algorithms, and achieve higher noise robustness.
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