Detail Enhancement of 3D Animation Images Based on Swarm Intelligence Algorithm

Authors

  • Jiujun Yang College of Art, Suzhou University of Science and Technology, Suzhou 215007, Jiangsu, China

Abstract

The absence of image details in the area of 3D animation design and generation causes the expression creation process of animation to be concealed, resulting in unnaturally image animation expressions. However, the traditional progression of 3D animation graphics has the issue of the inferior visual effect of image improvement. Hence, this paper proposes an Improved Particle Swarm Optimization based Image Enhancement Model (IPSO-IEM) to address the challenges of poor image effect and enhancement in conventional 3D image automatic generation. The data are taken from the iCartoon face dataset for 3D animation image enhancement. Firstly, the image can lose significant data when the size is reduced in 3D animation design. Therefore, the image is transformed from the spatial domain to achieve multi resolution. Secondly, Gamma adjustment is a proven method that creates a natural look and conserves the mean brightness of the picture with the choice of optimal gamma value. PSO selects the optimal gamma values and is utilized as a global search approach for the best optimum value and most improved image. In this research, an efficient fitness function is suggested to increase the performance of the PSO algorithm.

Keywords: 3D Animation Images, Image Enhancement, Particle Swarm Optimization, Swarm Intelligence

Cite As

J. Yang, "Detail Enhancement of 3D Animation Images Based on Swarm Intelligence Algorithm", 
Engineering Intelligent Systems, vol. 34 no. 2, pp. 211-219, 2026.


 

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Published

2026-03-01

Issue

Vol. 34 No. 2 (2026): International Journal of Engineering Intelligent Systems

Section

Article

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