Affiliations:
College of Materials Science and Art Design, Inner Mongolia Agricultural University, Hohhot, China
Correspondence:
[*]
Corresponding author. Huaqiong Duo, College of Materials Science and Art Design, Inner Mongolia Agricultural University, Hohhot 010018, China. E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Abstract: A novel enhancement method to improve resolution and contrast has been proposed to address the issues of blurring and distortion commonly encountered in traditional patterns. Initially, a discrete wavelet transform, a stationary wavelet transform, and an interpolation algorithm are used to obtain high-resolution images of traditional patterns. Subsequently, improved singular value matrix coefficients and reconstructed gamma function are used to enhance the image contrast to obtain high-resolution and contrast-enhanced patterns. Experimental results demonstrate the efficacy of this method, as evidenced by improved evaluation indexes, such as mean square error, peak signal-to-noise ratio, and structural similarity, in comparison to other existing methods. The proposed method effectively improves the quality of traditional patterns and offers significant contributions to research on the restoration and protection of traditional patterns.
Keywords: Traditional pattern enhancement, stationary wavelet transform, discrete
wavelet transform, singular value matrix, gamma function
