现代电子技术2024，Vol.47Issue(6)：161-164,4.DOI:10.16652/j.issn.1004-373x.2024.06.026
基于深度学习的多帧遥感降质图像三维重建算法
A deep learning based 3D reconstruction algorithm for multiframe degraded remote sensing images
石力源1
作者信息
- 1. 杭州电子科技大学, 浙江 杭州 310018
- 折叠
摘要
Abstract
In order to improve the contrast and image quality of multiframe degraded remote sensing images,a deep learning based 3D reconstruction algorithm for multiframe degraded remote sensing images is proposed.The trigonometric function transformation method combined with high pass filter is used to enhance the contrast of multiframe degraded remote sensing images.Based on a generative adversarial network that includes generators and discriminators,a self attention layer is introduced into the discriminator,and a residual module of the self attention mechanism is designed to generate a self attention generative adversarial network model.The enhanced image input model is learned and trained to obtain global features of multiple degraded remote sensing images,and then three-dimensional reconstruction of multiple degraded remote sensing images is achieved.The testing results show that the algorithm has good ability to enhance multi frame degraded remote sensing images and improve image contrast.The permeability indexs(PI)are all above 0.92,and the reconstruction effect is good.关键词
多帧遥感图像/降质图像/深度学习/三维重建/图像增强/生成对抗网络/自注意力层/全局特征Key words
multi frame remote sensing images/degraded images/deep learning/3D reconstruction/image enhancement/generative adversarial network/self attention layer/global features分类
信息技术与安全科学引用本文复制引用
石力源..基于深度学习的多帧遥感降质图像三维重建算法[J].现代电子技术,2024,47(6):161-164,4.
