Research On Adaptive Enhancement For Scanned Images Of Personnel Archives

Digital processing of archives is a labor-intensive work,which has the characteristics of large workload and high repetition.The personnel who have been engaged in this work for a long time are prone to irritability,which will affect the quality and effect of archives digital processing.Therefore,in the process of archives digital processing,how to use efficient technology to carry out large-scale,standardized enhancement processing on archives images is the problem that operators are more concerned about.In addition,in accordance with the requirements of the Technical Specifications for Digitalization of Cadre and Personnel Archives,archives digital processing should preserve the original appearance of paper archives images to the greatest extent,and at the same time avoid the problem of image distortion caused by the archives scanning process,so that the graphics and texts are more clearly identifiable.Starting from personnel archives,this thesis focuses on the relevant contents of the quality assessment and adaptive enhancement of scanned images of personnel archives.According to the requirements of Technical Specifications for Digitalization of Cadre Personnel Archives on the quality of archives images,this thesis proposes a quality assessment model for scanned images of personnel archives and an adaptive enhancement model,which aim to improve the efficiency of archives digital processing and improve the visual effects of digital archives images.The main research contents of this thesis are as follows:(1)This thesis designs a quality assessment model of scanned images of personnel archives.After quantifying the fuzziness,information gray and tilt angle of the scanned images of personnel archives,the comprehensive quality assessment of the images is carried out by the combination of deep learning and digital image processing technology,which can realize automatic batch processing,save the feature vector data of the archives images,and use it as the input of the adaptive enhancement model to lay the foundation for the adaptive enhancement of the images.(2)This thesis proposes an adaptive enhancement model for scanned images of personnel archives.The model carries out batch adaptive enhancement in three aspects:tilt correction,information gray and image deblurring of archives images.An image deblurring algorithm based on Gaussian pyramid is also proposed.Through experimental comparisons,it is concluded that the model has achieved the expected effect and is more prominent,and can meet the actual needs of current information construction projects.(3)This thesis establishes several datasets for the quality assessment and enhancement of scanned images of personnel archives are established.There are few existing special datasets for the research of scanning archives images.Combined with the research contents of this thesis and the implementation requirements of relevant projects,the datasets for quality assessment and adaptive enhancement for scanned images of personnel archives are designed and constructed,so as to solve the pain points and difficulties in the research of scanned images of personnel archives standardization and enhancement task.