Spatially adaptive total variation deblurring with split Bregman technique. Issue 6 (1st June 2018)

• Record Type: Journal Article
• Authors: Dodangeh, Mahdi; Figueiredo, Isabel N.; Gonçalves, Gil
• Is Part Of: IET image processing. Volume 12:Issue 6(2018)
• Page Start: 948
• Page End: 958
• Publication Date: 2018-06-01
• Subjects: image restoration -- gradient methods -- fast Fourier transforms; spatially adaptive total variation deblurring -- split Bregman technique -- spatial image information -- weighted total variation term -- image gradient -- split Bregman method -- discrete convolution transform -- fast Fourier transform -- standard image quality metrics; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.0302
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : In this study, the authors describe a modified non‐blind and blind deconvolution model by introducing a regularisation parameter that incorporates the spatial image information. Indeed, they have used a weighted total variation term, where the weight is a spatially adaptive parameter based on the image gradient. The proposed models are solved by the split Bregman method. To handle adequately the discrete convolution transform in a moderate time, fast Fourier transform is used. Tests are conducted on several images, and for assessing the results, they define appropriate weighted versions of two standard image quality metrics. These new weighted metrics clearly highlight the advantage of the spatially adaptive approach.