基于深度图像先验的散焦图像去模糊  

Defocused Image Deblurring Based on Depth Image Prior

作　　者：陈天明 CHEN Tianming(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学电子信息工程学院,江苏南京210016

出　　处：《现代信息科技》2020年第24期84-88,共5页Modern Information Technology

摘　　要：在散焦模糊图像中单个像素的模糊量由其景深确定,因此散焦模糊是空间变化的。传统的去模糊方法在解决这种空间变化的反卷积问题的时候,会在不同散焦程度的边界处产生明显的振铃效应。针对上述存在的问题,文章提出了基于深度图像先验的散焦图像去模糊算法。实验结果表明,与现有的散焦图像去模糊算法对比,该算法具有更好的去散焦模糊的性能。In a defocused and blurred image,the blur amount of a single pixel is determined by its depth of field,so the defocus blur is spatially variable.When traditional deblurring methods are used to solve the deconvolution problem of this kind of spatial variation,obvious ringing effect will appear at the boundary of different defocus degrees.Aiming at the above problems,this paper proposes a defocused image deblurring algorithm based on depth image prior.Experimental results show,comparing with the existing defocused image deblurring algorithm,this algorithm has better defocusing and deblurring performance.

关 键 词：散焦图像 去模糊 振铃效应 深度图像先验 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]