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用于焦平面偏振计划分的残差插值逐像素自适应迭代过程

Residual Interpolation Integrated Pixel-by-Pixel Adaptive Iterative Process for Division of Focal Plane Polarimeters.

作者信息

Yang Jie, Jin Weiqi, Qiu Su, Xue Fuduo, Wang Meishu

机构信息

MOE Key Laboratory of Optoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China.

出版信息

Sensors (Basel). 2022 Feb 16;22(4):1529. doi: 10.3390/s22041529.

DOI:10.3390/s22041529
PMID:35214435
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8874419/
Abstract

Residual interpolations are effective methods to reduce the instantaneous field-of-view error of division of focal plane (DoFP) polarimeters. However, their guide-image selection strategies are improper, and do not consider the DoFP polarimeters' spatial sampling modes. Thus, we propose a residual interpolation method with a new guide-image selection strategy based on the spatial layout of the pixeled polarizer array to improve the sampling rate of the guide image. The interpolation performance is also improved by the proposed pixel-by-pixel, adaptive iterative process and the weighted average fusion of the results of the minimized residual and minimized Laplacian energy guide filters. Visual and objective evaluations demonstrate the proposed method's superiority to the existing state-of-the-art methods. The proposed method proves that considering the spatial layout of the pixeled polarizer array on the physical level is vital to improving the performance of interpolation methods for DoFP polarimeters.

摘要

残差插值是减少焦平面分割(DoFP)偏振计瞬时视场误差的有效方法。然而,它们的引导图像选择策略并不恰当,且未考虑DoFP偏振计的空间采样模式。因此,我们基于像素化偏振器阵列的空间布局,提出了一种具有新引导图像选择策略的残差插值方法,以提高引导图像的采样率。通过所提出的逐像素自适应迭代过程以及最小化残差和最小化拉普拉斯能量引导滤波器结果的加权平均融合,插值性能也得到了提升。视觉和客观评估表明,该方法优于现有的最先进方法。所提出的方法证明,在物理层面考虑像素化偏振器阵列的空间布局对于提高DoFP偏振计插值方法的性能至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ef6/8874419/c23ecc4fdbb0/sensors-22-01529-g015.jpg
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7
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8
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