Dynamic reconstruction method of unmanned aerial vehicle aerial remote sensing image based on compressed sensing

Guangdi Ma, Weichen Yang
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Abstract

Aiming at the current problems of poor dynamic reconstruction of UAV aerial remote sensing images and low image clarity, the dynamic reconstruction method of UAV aerial remote sensing images based on compression perception is proposed. Construct a quality reduction model for UAV aerial remote sensing images, obtain image feature information, and further noise reduction preprocessing of UAV aerial remote sensing images to better improve the resolution, spectral and multi-temporal trends of UAV aerial remote sensing images, and effectively solve the problems of resource waste such as large amount of sampled data, long sampling time and large amount of data transmission and storage. Maximize the UAV aerial remote sensing images sampling rate, reduce the complexity of dynamic reconstruction of UAV aerial remote sensing images, and effectively obtain the research requirements of high-quality image reconstruction. The experimental results show that the proposed dynamic reconstruction method of UAV aerial remote sensing images based on compressed sensing is correct and effective, which is better than the current mainstream methods.
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基于压缩感知的无人机航空遥感图像动态重建方法
针对当前无人机航空遥感图像动态重建效果差、图像清晰度低等问题,提出了基于压缩感知的无人机航空遥感图像动态重建方法。构建无人机航空遥感图像质量降维模型,获取图像特征信息,对无人机航空遥感图像进行进一步的降噪预处理,以更好地提高无人机航空遥感图像的分辨率、光谱和多时相趋势,有效解决采样数据量大、采样时间长、数据传输存储量大等资源浪费问题。最大限度地提高无人机航空遥感图像的采样率,降低无人机航空遥感图像动态重建的复杂性,有效地获得高质量图像重建的研究要求。实验结果表明,本文提出的基于压缩感知的无人机航空遥感图像动态重建方法正确有效,优于当前主流方法。
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