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

^*Corresponding author for this work

School of Advanced Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original language	English
Title of host publication	2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings
Editors	Kostas Diamantaras, Aurelio Uncini, Francesco A. N. Palmieri, Jan Larsen
Publisher	IEEE Computer Society
ISBN (Electronic)	9781509007462
DOIs	https://doi.org/10.1109/MLSP.2016.7738902
Publication status	Published - 2016 Nov 8
Event	26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings - Vietri sul Mare, Salerno, Italy Duration: 2016 Sept 13 → 2016 Sept 16

Publication series

Name	IEEE International Workshop on Machine Learning for Signal Processing, MLSP
Volume	2016-November
ISSN (Print)	2161-0363
ISSN (Electronic)	2161-0371

Other

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

Keywords

Double Sparsity
Image Super Resolution
Sparse Coding

ASJC Scopus subject areas

Human-Computer Interaction
Signal Processing

Access to Document

10.1109/MLSP.2016.7738902

Cite this

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 [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).

Research output: Chapter in Book/Report/Conference proceeding › 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).

@inproceedings{91796e1e04f14e93b439fa00d0abac27,

title = "Doubly sparse structure in image super resolution",

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.",

keywords = "Double Sparsity, Image Super Resolution, Sparse Coding",

author = "Toshiyuki Kato and Hideitsu Hino and Noboru Murata",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings ; Conference date: 13-09-2016 Through 16-09-2016",

year = "2016",

month = nov,

day = "8",

doi = "10.1109/MLSP.2016.7738902",

language = "English",

series = "IEEE International Workshop on Machine Learning for Signal Processing, MLSP",

publisher = "IEEE Computer Society",

editor = "Kostas Diamantaras and Aurelio Uncini and Palmieri, {Francesco A. N.} and Jan Larsen",

booktitle = "2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings",

}

TY - GEN

T1 - Doubly sparse structure in image super resolution

AU - Kato, Toshiyuki

AU - Hino, Hideitsu

AU - Murata, Noboru

PY - 2016/11/8

Y1 - 2016/11/8

N2 - 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.

AB - 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.

KW - Double Sparsity

KW - Image Super Resolution

KW - Sparse Coding

UR - http://www.scopus.com/inward/record.url?scp=85002406492&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85002406492&partnerID=8YFLogxK

U2 - 10.1109/MLSP.2016.7738902

DO - 10.1109/MLSP.2016.7738902

M3 - Conference contribution

AN - SCOPUS:85002406492

T3 - IEEE International Workshop on Machine Learning for Signal Processing, MLSP

BT - 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings

A2 - Diamantaras, Kostas

A2 - Uncini, Aurelio

A2 - Palmieri, Francesco A. N.

A2 - Larsen, Jan

PB - IEEE Computer Society

T2 - 26th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016 - Proceedings

Y2 - 13 September 2016 through 16 September 2016

ER -

Doubly sparse structure in image super resolution

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this