(untitled) (Informatica, 2025)
Graphic design places emphasis on constructing visual aesthetics using computer-aided platforms, effectively shaping various design elements. Aim: A wavelet-based image processing technology solution is proposed for graphic design in response to the increasing demand for image-denoising quality in graphic design. The wavelet decision process is employed to transform the two-dimensional image structure, enhancing the threshold for generating wavelet coefficients, and evaluating them. Methodology: In order to enhance image removal and restoration, the author developed an adjustment model based on the wavelet decomposition scale, enabling the setting of a threshold for robust paper data collection. Results: Simulation verification and data analysis results indicate that the image restoration performance of the wavelet thresholding method and the adaptive thresholding method is nearly equivalent, surpassing both hard and soft thresholding methods. Conclusion: When compared to other methods, the adaptive wavelet threshold setting method employed by the author can enhance the peak signal-to-noise ratio by over 1.3 dB based on the adaptive threshold. Furthermore, the mean square error in image restoration has been reduced in comparison to existing methods, and the structural similarity has improved by more than 5% when contrasted with existing methods. It has been demonstrated that the proposed algorithm is superior in denoising and image restoration in comparison to existing algorithms, with adaptive thresholds effectively elevating the quality of image restoration.