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