{"type":"ScholarlyArticle","title":"Denoising and Completion of 3D Data via Multidimensional Dictionary Learning","authors":[{"name":"Zemin Zhang","slug":"zemin-zhang","given":"Zemin","family":"Zhang","affiliation":""},{"name":"Shuchin Aeron","slug":"shuchin-aeron","given":"Shuchin","family":"Aeron","affiliation":""}],"abstract":"In this paper a new dictionary learning algorithm for multidimensional data is proposed. Unlike most conventional dictionary learning methods which are derived for dealing with vectors or matrices, our algorithm, named K-TSVD, learns a multidimensional dictionary directly via a novel algebraic approach for tensor factorization as proposed in [Braman, 2010; Kilmer et al., 2011; Kilmer and Martin, 2011]. Using this approach one can define a tensor-SVD and we propose to extend K-SVD algorithm used for 1-D data to a K-TSVD algorithm for handling 2-D and 3-D data. Our algorithm, based on the idea of sparse coding (using group-sparsity over multidimensional coefficient vectors), alternates between estimating a compact representation and dictionary learning. We analyze our K-TSVD algorithm and demonstrate its result on video completion and video/multispectral image denoising.","doi":null,"url":"https://ijcai.org/proceedings/2016/338","pdf":"https://ijcai.org/proceedings/2016/0338.pdf","markdown":"https://ijcai.org/proceedings/2016/338.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/338","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":338,"pages":{"first":2371,"last":2376},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}