基于3线阵探测器的亚像元成像超分辨率重构

杨文波; 朱明; 刘志明; 陈东成

doi:10.3788/OPE.20142208.2247

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基于3线阵探测器的亚像元成像超分辨率重构

信息科学 | 更新时间：2020-08-13

- 基于3线阵探测器的亚像元成像超分辨率重构
- Super-resolution reconstruction of sub-pixel imaging achieved by three linear array detectors
- 光学精密工程 2014年22卷第8期页码：2247-2258
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院大学北京,中国,100049
  3. 中国科学院长春光学精密机械与物理研究所中国科学院航空光学成像与测量重点实验室,吉林长春,130033
- 作者简介：
- 基金信息：
  
  中国科学院航空光学成像与测量重点实验室开放基金面上项目（No.2012MS01）()
- DOI：10.3788/OPE.20142208.2247
  中图分类号： TP73;TP391
- 收稿日期：2013-06-26，
  
  修回日期：2013-08-07，
  
  纸质出版日期：2014-08-25
- 稿件说明：
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杨文波, 朱明, 刘志明等. 基于3线阵探测器的亚像元成像超分辨率重构[J]. 光学精密工程, 2014,22(8): 2247-2258

YANG Wen-bo, ZHU Ming, LIU Zhi-ming etc. Super-resolution reconstruction of sub-pixel imaging achieved by three linear array detectors[J]. Editorial Office of Optics and Precision Engineering, 2014,22(8): 2247-2258
杨文波, 朱明, 刘志明等. 基于3线阵探测器的亚像元成像超分辨率重构[J]. 光学精密工程, 2014,22(8): 2247-2258 DOI： 10.3788/OPE.20142208.2247.

YANG Wen-bo, ZHU Ming, LIU Zhi-ming etc. Super-resolution reconstruction of sub-pixel imaging achieved by three linear array detectors[J]. Editorial Office of Optics and Precision Engineering, 2014,22(8): 2247-2258 DOI： 10.3788/OPE.20142208.2247.

摘要

虽然增加探测器的时间和空间采样频率可以提高亚像元成像系统空间分辨率，但探测器采集到的数据易发生混叠，使重构得到的图像的分辨率无法达到理想值。本文以3片线阵探测器亚像元成像为基础，提出一种超分辨率重构算法。首先，在高分辨率网格上建立插值模型；然后，辨识插值重构图像在线阵列方向和扫描方向的模糊核，得到整幅图像的模糊核；最后，采用带有Neumman边界条件的梯度平滑正则化模型去除模糊，抑制振铃效应。实验结果表明，该算法使亚像元成像系统分辨率为单线阵探测器无过采样成像系统分辨率的2.6倍；与双线性插值法相比，平均灰度等级（GMG）提高了7.71。该算法可以进一步实现对更多片线阵探测器亚像元成像的超分辨率重构，获取更高的系统分辨率。

Abstract

The spatial resolution of a sub-pixel imaging system can be improved by increasing temporal and spatial sampling frequencies of detectors. However

the data collected by detectors are prone to aliasing and the resolution of reconstructed image is far away from the ideal value. In this paper

an algorithm of super-resolution reconstruction was proposed based on sub-pixel imaging achieved by three linear array detectors. Firstly

an interpolation model on high-resolution grid was established. Then

blur kernels in an image with high-resolution were identified in linear array and scanning directions respectively

from which the blur kernel in a frame was obtained. Finally

a gradient smoothing regularization model with Neumman boundary conditions was employed to deblur and inhibit ringing effects. Experimental results show that the system resolution of sub-pixel imaging by the proposed algorithm is 2.6 times that of non-oversampling imaging system of a single linear detector

and the Gray Mean Grade (GMG) is improved by 7.71 as compared to that of the bilinear interpolation algorithm. The algorithm can achieve super-resolution reconstruction for sub-pixel imaging systems with more linear array detectors and can obtain a higher system resolution.

关键词

Keywords

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