For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Iterative Reweighted Image Inpainting Using Robustness to Outliers of L1 Norm Minimization
Tomohiro TAKAHASHI Masaki NAKANISHI Kazunori URUMA Toshihiro FURUKAWA
D - Abstracts of IEICE TRANSACTIONS on Information and Systems (Japanese Edition)
Publication Date: 2017/10/01
Online ISSN: 1881-0225
Type of Manuscript: LETTER
image inpainting, AR model, robust estimation, weighted joint optimization,
Full Text(in Japanese): PDF(755.2KB)
>>Buy this Article
Conventional AR model based image inpainting algorithm do not perform well at non texture component in the image because these algorithms assume that an image is represented by an AR model. This letter formulates the image inpainting problem as joint optimization problem at modeling error and weighted TV norm.