Doubly sparse structure in image super resolution

Toshiyuki Kato; Hideitsu Hino; Noboru Murata

doi:10.1109/MLSP.2016.7738902

Doubly sparse structure in image super resolution

Toshiyuki Kato, Hideitsu Hino^*, Noboru Murata

^*この研究の対応する著者

先進理工学部

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

There are a large number of image super resolution algorithms based on the sparse coding, and some algorithms realize multi-frame super resolution. For utilizing multiple low resolution observations, both accurate image registration and sparse coding are required. Previous study on multi-frame super resolution based on sparse coding firstly apply block matching for image registration, followed by sparse coding to enhance the image resolution. In this paper, these two problems are solved by optimizing a single objective function. The proposed formulation not only has a mathematically interesting structure called the double sparsity, but also offers improved numerical performance.

本文言語	English
ホスト出版物のタイトル	2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings
編集者	Kostas Diamantaras, Aurelio Uncini, Francesco A. N. Palmieri, Jan Larsen
出版社	IEEE Computer Society
ISBN（電子版）	9781509007462
DOI	https://doi.org/10.1109/MLSP.2016.7738902
出版ステータス	Published - 2016 11月 8
イベント	26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings - Vietri sul Mare, Salerno, Italy 継続期間: 2016 9月 13 → 2016 9月 16

出版物シリーズ

名前	IEEE International Workshop on Machine Learning for Signal Processing, MLSP
巻	2016-November
ISSN（印刷版）	2161-0363
ISSN（電子版）	2161-0371

Other

Other	26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings
国/地域	Italy
City	Vietri sul Mare, Salerno
Period	16/9/13 → 16/9/16

ASJC Scopus subject areas

人間とコンピュータの相互作用
信号処理

文献へのアクセス

10.1109/MLSP.2016.7738902

他のファイルとリンク

引用スタイル

Kato, T., Hino, H., & Murata, N. (2016). Doubly sparse structure in image super resolution. In K. Diamantaras, A. Uncini, F. A. N. Palmieri, & J. Larsen (Eds.), 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings Article 7738902 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/MLSP.2016.7738902

Doubly sparse structure in image super resolution. / Kato, Toshiyuki; Hino, Hideitsu; Murata, Noboru.
2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. ed. / Kostas Diamantaras; Aurelio Uncini; Francesco A. N. Palmieri; Jan Larsen. IEEE Computer Society, 2016. 7738902 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2016-November).

研究成果: Conference contribution

Kato, T, Hino, H & Murata, N 2016, Doubly sparse structure in image super resolution. in K Diamantaras, A Uncini, FAN Palmieri & J Larsen (eds), 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings., 7738902, IEEE International Workshop on Machine Learning for Signal Processing, MLSP, vol. 2016-November, IEEE Computer Society, 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings, Vietri sul Mare, Salerno, Italy, 16/9/13. https://doi.org/10.1109/MLSP.2016.7738902

Kato T, Hino H, Murata N. Doubly sparse structure in image super resolution. In Diamantaras K, Uncini A, Palmieri FAN, Larsen J, editors, 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. IEEE Computer Society. 2016. 7738902. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP). doi: 10.1109/MLSP.2016.7738902

Kato, Toshiyuki ; Hino, Hideitsu ; Murata, Noboru. / Doubly sparse structure in image super resolution. 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings. editor / Kostas Diamantaras ; Aurelio Uncini ; Francesco A. N. Palmieri ; Jan Larsen. IEEE Computer Society, 2016. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP).

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abstract = "There are a large number of image super resolution algorithms based on the sparse coding, and some algorithms realize multi-frame super resolution. For utilizing multiple low resolution observations, both accurate image registration and sparse coding are required. Previous study on multi-frame super resolution based on sparse coding firstly apply block matching for image registration, followed by sparse coding to enhance the image resolution. In this paper, these two problems are solved by optimizing a single objective function. The proposed formulation not only has a mathematically interesting structure called the double sparsity, but also offers improved numerical performance.",

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Doubly sparse structure in image super resolution

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