Image processing algorithm of visual communication design based on deep learning in digital background

This study addresses the growing demand for image processing in visual communication design by proposing a deep learning (DL)-based algorithm to enhance creative efficiency and precision. The algorithm integrates DL technologies to optimize image processing workflows and applies them to design pract...

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Vydáno v:Discover Artificial Intelligence Ročník 5; číslo 1; s. 180 - 17
Hlavní autoři: Hou, Xugang, Liu, Qian, Zhang, Xiaoying
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.12.2025
Springer Nature B.V
Springer
Témata:
Accuracy
Algorithms
Artificial Intelligence
Automation
Computer Science
Convolutional neural network
Deep learning
Design
Designers
Digital Age
Digitalization
Efficiency
Engineering
Image processing algorithm
Innovations
Neural networks
Optimization
Technological change
Visual communication
Visual communication design
Deep learning
Digitalization
Image processing algorithm
Convolutional neural network
Visual communication design
ISSN:2731-0809, 2731-0809
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Shrnutí:This study addresses the growing demand for image processing in visual communication design by proposing a deep learning (DL)-based algorithm to enhance creative efficiency and precision. The algorithm integrates DL technologies to optimize image processing workflows and applies them to design practice, significantly improving processing efficiency. Experimental results demonstrate that this algorithm performs excellently in processing efficiency and user experience compared to traditional methods. Particularly in preventing overfitting, the algorithm exhibits stronger stability and lower error rates, further validating the potential of DL applications in visual communication design and image processing. Additionally, the system adapts well to diverse image data types and design styles, demonstrating excellent scalability that provides robust support for personalized design and innovation. The main contributions of this study include the introduction of DL technology to optimize image processing in visual communication design, thereby improving image quality and artistic expression. An innovative convolutional neural network-based algorithm is proposed to achieve more precise image processing. Simultaneously, efficient model training strategies are designed to address challenges in image resolution, color optimization, and content generation, enhancing processing efficiency and intelligent capabilities. These research outcomes hold significant application value across visual communication design, advertising creativity, and multimedia art fields.
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ISSN:2731-0809
2731-0809
DOI:10.1007/s44163-025-00430-6