应用于CMOS相机的暗电流建模代码
Pengjia
这里公布的是太原理工大学智能光学实验室研究的CMOS暗电流建模和坏像素识别方法所对应的样例代码，代码已经应用于一个商用卫星的数据处理任务中，并且展示了比较好的结果。本代码可作为启发，应用于不同类别的星载相机数据处理任务中。
文件
Code-A Data-Driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes.zip
5.76 kB
论文信息
论文标题:
A Data-Driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes
发表期刊:
AJ
标识符
CSTR:
11379.19.101387
DOI:
10.12149/101387
VO Identifier:
ivo://China-VO/paperdata/101387
发布时间:
2024-03-15
使用统计
总下载量
149
引用
Pengjia et al. 2024. Code for CMOS Dark Current Noise Modelling and Bad Pixel Detection. 版本 1.0. https://doi.org/10.12149/101387
@misc{10.12149/101387,
doi = {10.12149/101387},
url = {https://doi.org/10.12149/101387},
author = {Pengjia},
title = {Code for CMOS Dark Current Noise Modelling and Bad Pixel Detection},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2024}
}
doi = {10.12149/101387},
url = {https://doi.org/10.12149/101387},
author = {Pengjia},
title = {Code for CMOS Dark Current Noise Modelling and Bad Pixel Detection},
version = {1.0},
publisher = {Nataional Astronomical Data Center of China},
year= {2024}
}
版本