摘要
为了改善运动模糊图像复原的效果,构造了基于l0高阶全变差的盲复原数学模型。该模型在l0稀疏先验的基础上,引入了可降低振铃效应的高阶全变差正则化约束项,用以解决低阶全变差造成的虚假边缘问题。盲复原算法首先用半二次分裂对数学模型求解,然后根据先验信息对模型解约束,多次迭代得到中间潜像、模糊核,最后采用非盲从复原算法恢复图像。实验结果表明:提出的方法可突出边缘结构特征,有效改善盲复原图像的效果。
In order to improve the restoration effect of motion fuzzy images,a blind restoration mathematical model based on high-order total variation is constructed.Based on sparse priori,the regularization constraint term of high-order total variation which can reduce the ringing effect is introduced to solve the false edge problem caused by low-order total variation.The blind restoration algorithm first solves the mathematical model by semi-quadratic splitting,then constrains the solution of the model according to prior information,and obtains the intermediate latent image and fuzzy kernel through multiple iterations.Finally,the non-blind restoration algorithm is used to restore the image.Experimental results show that the proposed method can highlight the edge structure features and improve the blind restoration image effect effectively.
作者
高如新
郭凤云
李雪颖
GAO Ruxin;GUO Fengyun;LI Xueying(School of Mechanical and Power Engineering,Henan Polytechnic University,Jiaozuo 454000,China;School of Mechanical and Electrical Engineering,Yellow River Transportation College,Jiaozuo 454950,China)
出处
《传感器与微系统》
CSCD
2020年第12期143-145,共3页
Transducer and Microsystem Technologies
关键词
图像盲复原
高阶全变差
l0范数
先验
数学模型
image blind recovery
high order total variation
l0 norm
prior
mathematical model