• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2021, Vol. 43 ›› Issue (06): 1047-1051.

• 图形与图像 • 上一篇    下一篇

基于加权变换的蒙古族家具纹样增强研究

董霙达,张成涛,多化琼,杜豫怡   

  1. (内蒙古农业大学材料科学与艺术设计学院,内蒙古 呼和浩特 010018)
  • 收稿日期:2020-05-18 修回日期:2020-06-30 接受日期:2021-06-25 出版日期:2021-06-25 发布日期:2021-06-22
  • 基金资助:
    国家自然科学基金(31760185)

Enhancing Mongolian furniture patterns based  on weighted transform 

DONG Ying-da,ZHANG Cheng-tao,DUO Hua-qiong,DU Yu-yi#br#

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  1. (College of Material Science and Art Design,Inner Mongolia Agricultural University,Hohhot 010018,China)
  • Received:2020-05-18 Revised:2020-06-30 Accepted:2021-06-25 Online:2021-06-25 Published:2021-06-22

摘要: 针对蒙古族传统家具纹样模糊不清、边缘失真等问题,提出了基于加权变换的图像增强方法。首先将蒙古族家具纹样分解成RGB分量,
然后利用提升小波变换、平稳小波变换、插值算法和逆提升小波变换获得高分辨率纹样,最后利用加权变换函数对直方图进行修改,对贡献最小的直方图进行滤波,得到高分辨率和对比度增强的纹样。实验结果表明,该方法的评价指标峰值信噪比PSNR和结构相似性SSIM比传统直方图均衡化和双三次插值法的均有提升,有效地增强了蒙古族家具纹样。所提方法对传统蒙古族家具纹样的修复和保护研究具有重要价值。

关键词: 蒙古族家具纹样, 小波变换, 插值算法, 加权变换, 图像增强

Abstract: In order to solve the problems of fuzzy patterns and edge distortion of Mongolian traditional furniture, this paper proposes an image enhancement method based on weighted transformation. Firstly, Mongolian furniture patterns are decomposed into RGB components, and lifting wavelet transform, stationary wavelet transform, interpolation algorithm and inverse lifting wavelet transform are adopted to obtain the high- resolution patterns. Finally, the weighted transformation function is used to modify the histogram, and the histogram with the smallest contribution is filtered to obtain the high- resolution and contrast-enhanced patterns. This method is compared with the traditional histogram equalization and bicubic interpolation method. The experimental results show that the proposed method has better PSNR (Peak Signal to Noise Ratio) and SSIM (Structure Similarity Index) than the tradi-tional histogram equalization and bicubic interpolation methods, and can effectively enhance Mongolian furniture patterns. The proposed method  is of great value to the repair and protection of traditional Mongolian furniture patterns.



Key words: Mongolian furniture pattern, wavelet transform, interpolation algorithm, weighted transform, image enhancement