基于离散系数与Harris角点的微光像增强器闪烁噪声测试方法

刘峰阁; 苏天宁; 刘倍宏; 成帅; 朱荣胜; 姬明; 肖杰; 赵航; 张理淞; 常乐

基于离散系数与Harris角点的微光像增强器闪烁噪声测试方法

北方夜视技术股份有限公司, 云南昆明 650217

详细信息

作者简介:
刘峰阁（1985-），男，工程师，主要研究方向：非标专用设备设计开发。E-mail：lfg15925147665@163.com

中图分类号: TP391.4
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- 文章访问数: 51
- HTML全文浏览量: 4
- PDF下载量: 24
出版历程
- 收稿日期: 2023-09-30
- 修回日期: 2023-10-24
- 刊出日期: 2024-10-19

Flicker Noise Testing Based on a Discrete Coefficient and Harris Corner Point Detection for a Low-light Image Intensifier

North Night Vision Technology Co. Ltd., Kunming 650217, China

摘要

摘要:
为了弥补信噪比无法在二维空间上准确定位分析像增强器闪烁噪声特性的不足，本文针对像增强器闪烁噪声特性设计了一种基于离散系数与Harris角点检测的微光像增强器闪烁噪声测试方法。本方法采用基于Gsense400BSI CMOS图像传感器的高帧频图像采集系统实现与像增强器荧光屏余晖时间相匹配的闪烁噪声图像采集。通过对连续多帧采集到的图像进行像素级离散系数计算，热点图实现可视化，与Harris角点检测算法能够准确分析像增强器荧光屏各区域内的闪烁噪声情况并准确标记荧光屏上的高亮噪点。实验结果表明，该方法能够实现像增强器闪烁噪声的二维分析与定位，从而为像增强器性能优化以及噪声特性测试提供技术支持。
- 像增强器 /
- 闪烁噪声 /
- 离散系数 /
- 角点检测 /
- 噪声标记
Abstract:
To compensate for the insufficient signal-to-noise ratio, which cannot be accurately localized in two-dimensional space to analyze the flicker noise characteristics of an image intensifier, this study designs a low-light image intensifier flicker noise test method based on a discrete coefficient and Harris corner point detection for the image intensifier flicker noise characteristics. In this method, a high-frame-rate image acquisition system based on a Gsense400BSI CMOS image sensor was used to realize flicker noise image acquisition that matched the afterglow time of the fluorescent screen of the image intensifier. By calculating the pixel-level discrete coefficients of the images acquired from consecutive multiframes, a hotspot map was visualized. In addition, the Harris corner detection algorithm was used to accurately analyze the flicker noise in each region of the fluorescent screen of the image intensifier and mark the bright noise spots on the fluorescent screen. The experimental results show that this method can realize the two-dimensional analysis and localization of the flicker noise of the image intensifier and thus provide technical support for the performance optimization of the image intensifier and testing of noise characteristics.
- image intensifier /
- scintillation noise /
- dispersion coefficient /
- angular point detection /
- noise marker

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图 1 像增强器荧光屏噪声

Figure 1. Fluorescent screen noise of image intensifier

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图 2 高帧频图像采集系统实物

Figure 2. Photo of high frame rate image acquisition system

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图 3 闪烁噪声测试系统框图

Figure 3. Block diagram of flicker noise testing system

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图 4 不同照度下闪烁噪声图像

Figure 4. Flicker noise images under different illuminances

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图 5 闪烁噪声灰度热力分布图

Figure 5. Flicker noise grayscale thermal distribution map

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图 6 Moravec边缘检测原理^[14]

Figure 6. Moravec edge detection principle^[14]

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图 7 光源系统实物图

Figure 7. Photo of the light source system

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图 8 不同样片数量离散系数计算结果

Figure 8. Calculation results of dispersion coefficients for different sample quantities

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图 9 不同像增强器闪烁噪声与离散系数热力图

Figure 9. Thermogram of flicker noise and discrete coefficient of different image intensifiers

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图 10 不同照度下高亮噪声标记结果

Figure 10. High brightness noise labeling results under different illuminances

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图 11 不同像增强器高亮噪声标记结果

Figure 11. Different image intensifiers highlight noise labeling results

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表 1 像增强器离散系数与信噪比

Table 1 Discretization coefficient and signal-to-noise ratio of image intensifiers

Number	1	2	3	4	5	6
Coefficient of variation	0.4410	0.4242	0.5069	0.4294	0.4177	0.4850
SNR	24.28	24.66	22.28	24.55	26.08	22.51

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表 2 Harris角点检测与人工检测结果对比

Table 2 Comparison of Harris corner detection and manual detection results

Number	Noise type	Harris corner detection results	Manual detection results
1	Highlight noise	5.3	5.5
2	Highlight noise	4.7	4.4
3	Highlight noise	5.1	5.3
4	Highlight noise	4.2	4.5
5	Highlight noise	5.6	5.4
6	Highlight noise	4.1	4.2

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