红外焦平面阵列的盲元自适应快速校正

李凌霄; 冯华君; 赵巨峰; 徐之海; 李奇

doi:10.3788/OPE.20172504.1009

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红外焦平面阵列的盲元自适应快速校正

信息科学 | 更新时间：2020-07-07

- 红外焦平面阵列的盲元自适应快速校正
- Adaptive and fast blind pixel correction of IRFPA
- 光学精密工程 2017年25卷第4期页码：1009-1018
- 作者机构：
  
  浙江大学现代光学仪器国家重点实验室, 浙江杭州 310027
- 作者简介：
  
  [ "李凌霄 (1991-), 男, 重庆人, 博士研究生, 2014年于重庆大学获得学士学位, 现为浙江大学博士研究生, 主要从事红外成像、图像处理等方面的研究。E-mail:lilingxiao1@126.com" ]
  冯华君 (1963-), 男, 浙江余姚人, 教授, 博士生导师, 1982年于浙江大学获得硕士学位, 现为浙江大学光学成像工程研究所所长, 主要从事成像系统、遥感等方面的研究。E-mail:fenghj@zju.edu.cn FENG Hua-jun, E-mail:fenghj@zju.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(No.61475135)
- DOI：10.3788/OPE.20172504.1009
  中图分类号： TN21
- 收稿日期：2016-09-21，
  
  录用日期：2016-11-9，
  
  纸质出版日期：2017-04-25
- 稿件说明：
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李凌霄, 冯华君, 赵巨峰, 等. 红外焦平面阵列的盲元自适应快速校正[J]. 光学精密工程, 2017,25(4):1009-1018.

Ling-xiao LI, Hua-jun FENG, Ju-feng ZHAO, et al. Adaptive and fast blind pixel correction of IRFPA[J]. Optics and precision engineering, 2017, 25(4): 1009-1018.
李凌霄, 冯华君, 赵巨峰, 等. 红外焦平面阵列的盲元自适应快速校正[J]. 光学精密工程, 2017,25(4):1009-1018. DOI： 10.3788/OPE.20172504.1009.

Ling-xiao LI, Hua-jun FENG, Ju-feng ZHAO, et al. Adaptive and fast blind pixel correction of IRFPA[J]. Optics and precision engineering, 2017, 25(4): 1009-1018. DOI： 10.3788/OPE.20172504.1009.

摘要

为实现红外焦平面阵列（IRFPA）盲元的自适应快速校正，本文设计了一种基于三梯度阈值检测的快速盲元校正方法。先通过优化L0范式的约束方程消除图中的非均匀条纹，排除干扰，再对水平、竖直和对角3个方向进行梯度阈值检测，找到盲元位置点，并与中值滤波结果进行点对点匹配，剔除误检测点，最后通过局部中值滤波完成盲元校正。依据盲元的缓变特性，通过合理更新盲元模板实现了单帧和序列图像的快速盲元校正。实验结果表明：相比于传统方法，本文方法的信噪比（SNR）和峰值信噪比（PSNR）提高了10~14 dB，结构相似度指标（SSIM）提高了0.01~0.02，对图像中的随机和连续盲元的校正效果都很好，同时运算速度得到了大大提升，在保证图像质量指标的情况下速度提升了3~10倍，可以在到实际红外系统中实现动态检测和实时处理。

Abstract

A fast blind pixel correction method based on three-gradient threshold detection was designed in this paper

to achieve adaptive and fast blind pixel correction of the Infrared Focal Plane Array (IRFPA). First

a constraint equation through optimization of L0 paradigm was used to eliminate the interference of non-uniform stripe; then gradient threshold detection was respectively conducted in the horizontal

vertical and diagonal directions to find out the position of the blind pixel

thus through a point-to-point matching with the median filtering results to remove the inaccurate detecting point; finally

blind pixel correction was completed through local median filtering. In the process

reasonable updating of the blind pixel template

based on slow variation of blind pixel

was carried out to achieve fast blind pixel correction of single-frame and sequential images. The results show that compared with traditional method

signal-to-noise ratio (SNR) and peak signal-to-noise ratio (PSNR) achieved by using this proposed method is improved by 10~14dB

with the structured similarity (SSIM) index improved by 0.01~0.02; both random blind pixel and continuous blind pixel in the images can be effectively corrected

and the computing speed is dramatically improved

with a speed advantage of 3~10 times while ensuring the image quality. Hence

such proposed method can be used to achieve dynamic detection and real-time processing in actual infrared system.

关键词

Keywords

references

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