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A Method for Generating Advertising Design Images Based on Hierarchical Features and Simulated Annealing Algorithm

Zhang Jian

Machine Graphics and Vision

2025

Vol. 34, No. 4

65--84

With the development of intelligent design and computer-aided design technology, advertising image generation has gradually received attention and over 70% of digital advertisers regard automated creative generation as a key direction for improving efficiency and precision delivery. To address the shortcomings of existing advertising design methods in feature extraction and optimization efficiency, a novel advertising design image generation method combining hierarchical feature extraction and simulated annealing algorithm optimization is proposed. Research is based on a hierarchical feature model to extract multi-scale semantic information from advertising images, and optimize layout through simulated annealing algorithm to improve the visual consistency of design images. The experiment outcomes show that the raised model has the highest mean fitness, especially in the first set of hyperparameter settings, with mean fitness values of 3.00 and 2.95 on the training and testing sets, respectively. Meanwhile, the standard deviation and coefficient of variation are significantly lower than for other algorithms, with minimal fluctuations and the strongest robustness. In addition, among the three types of advertising images for product promotion, brand promotion, and directive sign advertisement, the generated advertising images have significant advantages in visual clarity, perceptual quality, and other aspects. As shown in the directive sign advertisement, the mean square error, peak signal-to-noise ratio, structural similarity, and learning perceptual image patch similarity of this model are 0.025, 66.97,0.67, and 0.10, respectively, which are significantly better than the other two comparison methods. The research results indicate that the raised model is suitable for scenarios that require high-precision image generation, providing an effective solution for intelligent advertising generation.