一种面向图像传输的语义光通信系统和方法数据集

本数据集中的发明专利利用神经网络对图像信息进行压缩编码，在低信噪比，带宽受限，距离较长的直调直检系统中的光传输场景下，可以实现对图片信息的高保真传输。利用python软件进行图像编解码，使用VPI仿真软件进行图片的光传输仿真。采用Origin软件对获取的数据作图，并获得专利中的相关仿真结果图片。数据量为：1.8MB

The invention patents included in this dataset employ neural networks to compress and encode image information. High-fidelity transmission of image data can be achieved in optical transmission scenarios of direct-modulation direct-detection systems with low signal-to-noise ratio (SNR), limited bandwidth and long transmission distances. Image encoding and decoding were implemented using Python software, and optical transmission simulations of images were conducted with VPI simulation software. The acquired data were plotted using Origin software, and relevant simulation result images from the patents were obtained. The total data volume of this dataset is 1.8 MB.

搜集汇总

背景与挑战

背景概述

该数据集基于发明专利，专注于图像传输的语义光通信系统，利用神经网络进行图像压缩编码，旨在实现在低信噪比、带宽受限和长距离的光传输场景下的高保真图像传输。数据集包含仿真结果图片和相关数据，总数据量为2.69MB，涉及电子与通信技术领域，由北京邮电大学发布，并支持国家重点研发计划项目。