Optimization and Implementation of Deep Learning-based Image Processing Algorithm for Communication Engineering
This paper discusses the optimization and implementation of image processing algorithms in the field of communication engineering based on deep learning technology.Deep learning has shown a powerful ability in the field of image processing,but the specific application in communication engineering is still in the early stage of development.For this reason,this paper proposes an image processing algorithm optimization method that comprehensively considers the needs of communication engineering and is implemented by deep learning technology.First,the special needs and challenges of image processing in communication engineering are analyzed,and then an optimization strategy for these needs is proposed,including but not limited to transmission efficiency,anti-interference ability and real-time performance.Then,a deep learning-based image processing model is designed,and its performance advantages in communication engineering are experimentally verified.Finally,the proposed method is deployed in a real communication system and the performance is evaluated and compared.The experimental results show that this method achieves significant optimization results in communication engineering image processing tasks,and is practical and feasible.
deep learningcommunication engineeringimage processingalgorithmcommunication systemanti-interference capability
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