Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network

Atmospheric Turbulence Intensity Image Acquisition Method Based on Convolutional Neural Network

An algorithmic model of a neural network with channel attention and spatial attention (CASANet) is proposed to estimate the value of atmospheric coherence length, which in turn provides a quantitative description of atmospheric turbulence intensity. By processing the acquired spot image data, the ch...

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Bibliographic Details
Main Authors: Yuan Mu, Liangping Zhou, Shiyong Shao, Zhiqiang Wang, Pei Tang, Zhiyuan Hu, Liwen Ye
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
Subjects:
atmospheric turbulence
neural network
image processing
Online Access:https://www.mdpi.com/2072-4292/17/1/103
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