基于深度学习算法的图像超分辨率重建研究
Research on Image Super-resolution Reconstruction Based on Deep Learning Algorithm
王嘉进1
作者信息
- 1. 闽南理工学院,福建 泉州 362700
- 折叠
摘要
该文首先概述了基于深度学习算法的图像超分辨率内容,深入分析了基于多层次特征提取的图像超分辨率重建算法理论方法,并通过图像重建技术与软件设计探讨了算法应用实践过程.最后,针对当前图像超分辨率重建存在的问题提出了一系列改进策略,以期为探索基于深度学习算法的图像超分辨率重建技术在实际应用中的可行性和有效性,为图像处理领域的发展和应用提供新的思路和方法.
Abstract
This paper firstly summarizes the content of image super-resolution based on deep learning algorithm,deeply analyzes the theory and method of image super-resolution reconstruction algorithm based on multi-level feature extraction,and discusses the application process of algorithm through image reconstruction technology and software design.Finally,a series of improvement strategies are proposed to solve the existing problems in image super-resolution reconstruction,in order to explore the feasibility and effectiveness of image super-resolution reconstruction technology based on deep learning algorithm in practical applications,and to provide new ideas and methods for the development and application of image processing.
关键词
深度学习/图像超分辨率/重建算法/算法模型Key words
deep learning/image super resolution/reconstruction algorithm/algorithm model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据