基于AI的遥感影像条带噪声滤波方法研究
Research on AI Based Band Noise Filtering Method for Remote Sensing Images
江海宝 1皮原征1
作者信息
- 1. 广东省国土资源测绘院,广东 广州 510700
- 折叠
摘要
研究基于人工智能(Artificial Intelligence,AI)的遥感影像条带噪声滤波方法,旨在提高条带噪声去除的精准度与效率.通过卷积神经网络(Convolutional Neural Networks,CNN)提取噪声特征,并结合生成对抗网络分离噪声与信号,利用强化学习优化滤波参数.实验表明,该方法在峰值信噪比、结构相似性等指标上均优于传统方法,特别是在不同噪声强度下保持了较高的图像质量.
Abstract
In order to improve the accuracy and efficiency of stripe noise removal,the stripe noise filtering method of remote sensing images based on Artificial Intelligence(AI)is studied.The noise features are extracted by Convolutional Neural Networks(CNN),and the noise and signal are separated by combining with the generated countermeasure network,the filtering parameters are optimized by reinforcement learning.Experiments show that this method is superior to traditional methods in terms of peak signal-to-noise ratio and structural similarity,especially in maintaining high image quality under different noise intensities.
关键词
遥感影像/条带噪声/深度学习Key words
remote sensing images/stripe noise/deep learning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据