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Research on Creativity Generation and Innovative Expression Strategies of Graphic Design Based on Graphic Processing Technology

Dongsong Zhang

Dongsong Zhang

Quzhou UniversityQuzhou, China
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Zhang, Dongsong
, 
Wentao Chen

Wentao Chen

Quzhou UniversityQuzhou, China
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Chen, Wentao
, 
Mingjian Xu

Mingjian Xu

Quzhou UniversityQuzhou, China
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Xu, Mingjian
 y 
Shenghao Zhu

Shenghao Zhu

Quzhou UniversityQuzhou, China
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Zhu, Shenghao
  
24 mar 2025
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Publicado en línea: 24 mar 2025
Recibido: 17 nov 2024
Aceptado: 15 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0740
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© 2025 Dongsong Zhang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

The dynamic graphics design factor is based on perceptual fluency
The dynamic graphics design factor is based on perceptual fluency

Consistency test results

The best design for dynamic graphics based on perceptual fluency Perceptual attribute Perceptual experience attribute Cognitive attribute Aesthetic attribute
λmax 4.682 6.357 4.365 4.052 4.139
CI 0.021 0.089 0.007 0.004 0.008
RI 0.904 1.135 0.634 0.337 0.563
CR 0.025 0.084 0.025 0.005 0.002

The average PSNR value and SSIM values on the test set

Data set Scale Bicubic VDSR DRCN IDN Ours
Set5 x2 35.25/0.9321 45.25/0.9361 41.85/0.9212 41.52/0.8695 46.77/0.9525
x3 30.11/0.8047 34.61/0.9112 37.16/0.9103 41.06/0.9211 43.61/0.9301
x4 28.36/0.8124 41.56/0.8241 39.42/0.8893 32.42/0.8694 47.15/0.9052
Set14 x2 31.75/0.7216 32.65/0.9159 32.76/0.7214 36.12/0.7953 40.29/0.9332
x3 28.98/0.7178 36.89/0.7549 31.52/0.8245 35.12/0.8841 37.62/0.9124
x4 29.34/0.8542 31.21/0.8121 29.98/0.7936 35.43/0.9016 33.12/0.9175
BSD100 x2 30.15/0.7893 30.54/0.8512 32.96/0.8121 32.16/0.7715 36.79/0.8971
x3 35.62/0.8497 29.68/0.7562 32.56/0.8246 33.79/0.8925 38.44/0.9015
x4 38.54/0.8511 30.24/0.8266 29.81/0.9013 32.15/0.9196 40.98/0.9127
Urban100 x2 31.89/0.8647 29.79/0.8978 28.64/0.8694 33.78/0.9101 35.67/0.9134
x3 29.18/0.7412 31.52/0.7552 29.43/0.8941 35.88/0.9133 34.05/0.9217
x4 25.64/0.6689 28.34/0.7496 30.14/0.8236 30.21/0.8264 33.67/0.8596

Questionnaire data

Evaluation dimension Evaluation weight User evaluation (mean) Evaluation result
Perceptual attribute 0.3561 3.57 25.43
Perceptual experience attribute 0.1147 3.67 8.42
Cognitive attribute 0.2414 4.11 19.84
Aesthetic attribute 0.2878 3.82 21.99
The app’s dynamic graphics design score 75.68

Compare the operating time of different models (s)

Data set Scale VDSR DRCN IDN Ours
Set5 x2 0.053 0.755 0.019 0.025
x3 0.068 0.715 0.012 0.019
x4 0.056 0.725 0.009 0.017
Set14 x2 0.135 1.623 0.035 0.032
x3 0.147 1.528 0.018 0.017
x4 0.098 1.631 0.012 0.014
BSD100 x2 0.065 0.998 0.019 0.006
x3 0.076 0.989 0.015 0.015
x4 0.072 0.993 0.007 0.008
Urban100 x2 0.468 5.631 0.084 0.074
x3 0.512 5.248 0.036 0.063
x4 0.479 5.123 0.052 0.029
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Ciencias de la vida, Ciencias de la vida, otros, Matemáticas, Matemáticas aplicadas, Matemáticas generales, Física, Física, otros
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