吉林大学学报(信息科学版) ›› 2026, Vol. 44 ›› Issue (1): 226-232.

• • 上一篇    

图书馆电子扫描档案信息自适应无迹卡尔曼滤波去噪算法

邓 哲1 , 戴 鑫2   

  1. 1. 江苏经贸职业技术学院 后勤保障与基建处, 南京 211168; 2. 南京工程学院 后勤管理处, 南京 211167
  • 收稿日期:2025-04-09 出版日期:2026-01-31 发布日期:2026-02-04
  • 作者简介: 邓哲(1985— ), 女, 江苏溧阳人, 江苏经贸职业技术学院馆员, 主要从事档案管理研究, (Tel)86-17715283550(E-mail) wanzi121004@ 163. com
  • 基金资助:
    江苏省科技厅自然科学基金项目(HXJKY8134) 

Adaptive Unscented Kalman Filter Denoising Algorithm for Electronic Scanned Archive Information in Libraries

DENG Zhe1 , DAI Xin   

  1. 1. Office of Logistics Support and Infrastructure Development, Jiangsu Vocational Institute of Commerce, Nanjing 211168, China; 2. Logistics Management Office, Nanjing Institute of Technology, Nanjing 211167, China
  • Received:2025-04-09 Online:2026-01-31 Published:2026-02-04

摘要: 现有电子扫描档案信息去噪方法, 难以应对扫描档案中混合出现的墨渍、 折痕、 纸张纹理等复杂噪声。 且在去噪过程中会导致文字边缘模糊。 为此, 设计图书馆电子扫描档案信息自适应无迹卡尔曼滤波去噪算法。 将图书馆电子扫描档案信息划分为多个子区域, 计算各子区域的信息熵。 对信息熵较低的子区域完成线性 变换, 通过调整像素值的范围和偏移量增加像素多样性, 提高该图书馆电子扫描档案区域信息熵。 基于信息熵 优化后的图书馆电子扫描档案信息, 利用自适应无迹卡尔曼滤波去噪算法实现图书馆电子扫描档案信息去噪。 测试结果为设计方法在处理后的图像中保留了更多的细节, 同时有效地去除了噪声, 使得图像整体更加清晰, 设计方法的文本可读性指数(TLI: Text Legibility Index) 值整体高于 0. 96, 历史特征保留度( HFP: Historical Feature Preservation)值最高达到 0. 97, 说明该算法能为图书馆电子扫描档案的数字化保护和利用提供有效的 技术支持。

关键词: 图书馆, 电子扫描, 档案信息, 自适应无迹卡尔曼滤波去噪, 观测方程, 状态方程

Abstract: The existing electronic scanning archive information denoising methods are difficult to cope with complex noise such as ink stains, greases, and paper textures mixed in the scanned archives. During the denoising process, it can cause blurry edges of the text. An adaptive unscented Kalman filter denoising algorithm is designed for electronic scanning of archival information in libraries. is divided The electronic scanned archive information of the library is devided into multiple sub regions and the information entropy of each sub region is calculated. Linear transformation is performed on sub regions with low information entropy, pixel diversity is increased by adjusting the range and offset of pixel values, and the information entropy of the electronic scanning archive area in the library improved. Based on information entropy optimization, the library electronic scanned archive information is denoised using an adaptive unscented Kalman filter denoising algorithm. The test results show that the method preserves more details in the processed images while effectively removing noise, making the overall image clearer. The TLI(Text Legibility Index) value of the design is generally higher than 0. 96, and the HPF(Historical Feature Preservation) value of the design method reaches a maximum of 0. 97, indicating that the algorithm can provide effective technical support for the digital protection and utilization of electronic scanned archives in libraries.

Key words: library, electronic scanning, archive information, adaptive unscented kalman filter for noise reduction, observation equation, equation of state

中图分类号: 

  • TP183