重庆工商大学学报（自然科学版）2025，Vol.42Issue(4)：36-43,8.DOI:10.16055/j.issn.1672-058X.2025.0004.005
基于即插即用的盲二值图像去模糊算法
Blind Binary Image Deblurring Using Plug-and-Play Algorithm
摘要
Abstract
Objective A special class of images,such as text,barcodes,and fingerprint images,plays a significant role in digital systems.The main characteristic of these images is that their pixel values can only take values from a binary set.To address the problem of recovering degraded binary images containing additive noise and motion blur,a new blind image deblurring algorithm based on a plug-and-play framework was proposed.Methods This method combined denoiser prior and binary prior knowledge in the blind deblurring model,which utilizes advanced denoisers(e.g.,data-driven denoisers)while equipping the recovered latent images with binary features.By improving the recovery quality of the latent image,the accuracy of the estimated blur kernel was further improved,which in turn enhanced the final recovery results.In addition,in order to further enhance the pixel-value distribution characteristics of the recovered images,a thresholding operation was applied to the recovered images to restrict the pixel-value distribution of the recovered images to a specific set of binary values.Results The results of a large number of numerical experiments showed that this method has good application in the task of processing blurred binary images with noise and motion blur,and its performance is better than the existing traditional algorithms.Conclusion Therefore,the blind deblurring algorithm combining denoiser prior and binary prior knowledge can effectively restore binary images degraded by additive noise and motion blur.关键词
二值图像/图像盲去模糊/即插即用/舍入算子Key words
binary image/blind image deblurring/plug-and-play/rounding operator分类
信息技术与安全科学引用本文复制引用
杨雪松,何亮田..基于即插即用的盲二值图像去模糊算法[J].重庆工商大学学报（自然科学版）,2025,42(4):36-43,8.基金项目
国家自然科学基金青年项目(12001005) （12001005）
安徽省科技厅自然科学基金青年项目(2008085QF286) （2008085QF286）
安徽省教育厅高校自然科学研究重点项目(KJ2019A0032). （KJ2019A0032）
