Title: Deep learning driven dynamic image processing in film and television animation

Authors: Ran Zhang

Addresses: Henan Institute of Technology, Xinxiang, Henan, China

Abstract: The growing development of film and television animation makes the data of dynamic image become more-huge, and the dynamic image processing becomes more complex. This paper proposes an HDR-Net method for dynamic image processing based on multi-disciplinary fields such as image processing, film and television animation and deep learning. HDR-Net is improved by U-Net, which has less computation. At the same time, global feature modules are added to process large areas of weak texture areas. In addition, this paper has conducted a great many simulation experimentations on the HDR-Net, the traditional SegNet and U-SegNet methods. It also conducts functional tests and performance tests on the data set for the above methods. The results show that the HDR-Net has higher prediction accuracy and better sensory effects when it is used to process dynamic image in film and television animation.

Keywords: image processing; deep learning; HDR-Net method; film and television animation.

DOI: 10.1504/IJCAT.2025.150335

International Journal of Computer Applications in Technology, 2025 Vol.77 No.3/4, pp.274 - 282

Received: 31 Oct 2024
Accepted: 15 Aug 2025
Published online: 09 Dec 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article