Study on Ghibli Color Sensitivity Reproduced in AI Image Generation : An Analysis of Visual Similarities with Hayao Miyazaki Animation Posters

Since the 21st century, image generation technologies have evolved beyond imitating human intuition to structuring visual emotions through artificial intelligence (AI). This study examines how the color sensibility embedded in Studio Ghibli’s animation posters is reproduced by generative AI. We conducted a quantitative color analysis of 20 representative posters directed by Hayao Miyazaki using the HSL (Hue, Saturation, Lightness) model, and compared the results with 16 AI-generated images produced under the same conditions. The analysis revealed that Ghibli posters consistently adopt a low-saturation color strategy centered on turquoise and ocher tones to evoke emotional immersion, while AI images tended to replicate similar chromatic structures. However, limitations emerged in the narrative flow and contextual depth of emotions, as the nuanced interaction between color and emotional progression was less sophisticated than that achieved by human designers’ intuition. User evaluations also indicated that while participants perceived strong visual similarity between the original and AI-generated images, they reported lower satisfaction regarding emotional diversity. Overall, the study demonstrates that AI-generated “Ghibli-style” images go beyond mere visual imitation by forming an independent emotional structure, yet remain constrained in capturing narrative depth. These findings provide a theoretical basis for understanding both the potential and limitations of algorithmic reproduction of color sensibility, and suggest practical implications for applying generative AI technologies in emotional design.

Authors

Publication Details

Journal
Korea Institute of Design Research Society
Published
2025-09-30
DOI
https://doi.org/10.46248/kidrs.2025.3.48
Primary Topic
Color Science and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on Ghibli Color Sensitivity Reproduced in AI Image Generation : An Analysis of Visual Similarities with Hayao Miyazaki Animation Posters

Zehan Wu, Ji Yun Maeng
Korea Institute of Design Research Society
Color Science and Applications
article

Study on Ghibli Color Sensitivity Reproduced in AI Image Generation : An Analysis of Visual Similarities with Hayao Miyazaki Animation Posters

Zehan Wu, Ji Yun Maeng
article en

Abstract

Since the 21st century, image generation technologies have evolved beyond imitating human intuition to structuring visual emotions through artificial intelligence (AI). This study examines how the color sensibility embedded in Studio Ghibli’s animation posters is reproduced by generative AI. We conducted a quantitative color analysis of 20 representative posters directed by Hayao Miyazaki using the HSL (Hue, Saturation, Lightness) model, and compared the results with 16 AI-generated images produced under the same conditions. The analysis revealed that Ghibli posters consistently adopt a low-saturation color strategy centered on turquoise and ocher tones to evoke emotional immersion, while AI images tended to replicate similar chromatic structures. However, limitations emerged in the narrative flow and contextual depth of emotions, as the nuanced interaction between color and emotional progression was less sophisticated than that achieved by human designers’ intuition. User evaluations also indicated that while participants perceived strong visual similarity between the original and AI-generated images, they reported lower satisfaction regarding emotional diversity. Overall, the study demonstrates that AI-generated “Ghibli-style” images go beyond mere visual imitation by forming an independent emotional structure, yet remain constrained in capturing narrative depth. These findings provide a theoretical basis for understanding both the potential and limitations of algorithmic reproduction of color sensibility, and suggest practical implications for applying generative AI technologies in emotional design.

Korea Institute of Design Research SocietyVol. 10(3)
Openalex Percentile: Top 77%
Color Science and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.