吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (4): 701-708.

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基于小波域的数字化媒体图像自适应模糊去重算法

 刘家齐   

  1. 西北大学现代学院 电影学院, 西安 710069
  • 收稿日期:2022-06-13 出版日期:2023-08-16 发布日期:2023-08-17
  • 作者简介:刘家齐(1989— ), 女, 西安人, 西北大学讲师, 主要从事数字媒体艺术研究, ( Tel) 86-15202920485 ( E-mail) ljqq22@ 126. com。
  • 基金资助:
    陕西省教育厅专项科研计划基金资助项目(21JK0386) 

Adaptive Blur and Deduplication Algorithm for Digital Media Image Based on Wavelet Domain

LIU Jiaqi   

  1. Film Academy, Modern College of Northwest University, Xi’an 710069, China
  • Received:2022-06-13 Online:2023-08-16 Published:2023-08-17

摘要: 针对目前图像的模糊去重方法存在处理后图像不清晰、 质量不高的问题, 提出了基于小波域的数字化 媒体图像自适应模糊去重算法。 首先通过小波域方法对数字化媒体图像完成去噪处理; 其次利用逐步标注显 著区域方法将数字化媒体图像分成保护与非保护区域, 其中保护区域即为显著区域; 最后利用显著性正则化处 理图像, 完成图像的自适应模糊去重算法。 实验结果表明, 基于小波域的数字化媒体图像自适应模糊去重算法 处理后的图像噪声低、 质量高、 图像信息丰富, 清晰度好。 

关键词: 数字化媒体图像, 小波域, 去噪处理, 图像分块, 自适应模糊去重 

Abstract: The propagation of digital media images is widely used in daily life. At present, the fuzzy image de duplication method still has the problems of unclear image and low quality after processing. In order to solve the problems, an adaptive fuzzy de duplication algorithm for digital media images based on wavelet domain is proposed. Firstly, the digital media image is denoised by wavelet domain method. Secondly, the digital media image is divided into protected area and unprotected area by using the method of gradually labeling significant area, in which the protected area is the significant area. Finally, the image is processed by significance regularization, and the image adaptive fuzzy de duplication algorithm is completed. The experimental results show that the image noise is low, the image quality is high, the image information is rich, and the definition is good. 

Key words:  digital media image, wavelet domain, denoising, image segmentation, adaptive blurring and deduplication

中图分类号: 

  • TP391. 41