Proceedings of the 3rd International Conference on Educational Innovation and Multimedia Technology, EIMT 2024, March 29–31, 2024, Wuhan, China

Research Article

The Application of AI Technology in Post-Processing of Photography

Download53 downloads
  • @INPROCEEDINGS{10.4108/eai.29-3-2024.2347637,
        author={Wenying  Guo and Wenjie  Zhang and Jiaxing  Zhang and Shiwei  Zhang and Ling  Jin},
        title={The Application of AI Technology in Post-Processing of Photography},
        proceedings={Proceedings of the 3rd International Conference on Educational Innovation and Multimedia Technology, EIMT 2024, March 29--31, 2024, Wuhan, China},
        publisher={EAI},
        proceedings_a={EIMT},
        year={2024},
        month={6},
        keywords={photography post-processing ai image processing computational intelligence and deep learning general and reference},
        doi={10.4108/eai.29-3-2024.2347637}
    }
    
  • Wenying Guo
    Wenjie Zhang
    Jiaxing Zhang
    Shiwei Zhang
    Ling Jin
    Year: 2024
    The Application of AI Technology in Post-Processing of Photography
    EIMT
    EAI
    DOI: 10.4108/eai.29-3-2024.2347637
Wenying Guo1,*, Wenjie Zhang1, Jiaxing Zhang1, Shiwei Zhang1, Ling Jin1
  • 1: Tianjin University of Technology Main Campus
*Contact email: wenyingguo@stud.tjut.edu.cn

Abstract

In this study, we conducted an in-depth investigation into the application of AI technology in post-processing of photography. We have categorized AI applications into three distinct groups: AI Enhancement and Restoration, AI Image Recognition, and AI Generation. AI Enhancement and Restoration techniques possess remarkable advantages in improving image quality. Within this domain, we have delved into the remarkable optimization effects that can be achieved through techniques such as defogging, super-resolution, colorizing old photos, and removing scratches. Subsequently, we examined the utilization of AI Image Recognition technology in post-processing of photography. We emphasized its application in areas such as topic detection, background elimination, and face recognition. Finally, we examined the performance of AI Generation in generating images. These images not only exhibit a high degree of realism but also have the ability to achieve effects such as style conversion based on user preferences, significantly enhancing the diversity of visual expression.