Sparse representation approach to inverse halftoning in terms of DCT dictionary

Yuhri Ohta; Toshiaki Aida

doi:10.1109/ICCAS.2014.6987771

Sparse representation approach to inverse halftoning in terms of DCT dictionary

Yuhri Ohta, Toshiaki Aida

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

6 Citations (Scopus)

Abstract

The problem of inverse halftoning is approached on the basis of compressed sensing, which enables us to make significantly efficient inference through the sparse representation of data to be inferred. For this purpose, we have adopted a DCT dictionary as a basis to represent image patches. In the Bayesian formulation of the problem taking the sparse representation into account, the MAP estimate is found to lead to an inverse halftoning algorithm which can be interpreted as a linear programming problem. Numerical simulations have successfully confirmed the effectiveness of the algorithm, which allows us to conclude that the compressed sensing approach is efficient to the problem of inverse halftoning.

Original language	English
Title of host publication	International Conference on Control, Automation and Systems
Publisher	IEEE Computer Society
Pages	1377-1380
Number of pages	4
ISBN (Electronic)	9788993215069
DOIs	https://doi.org/10.1109/ICCAS.2014.6987771
Publication status	Published - Dec 16 2014
Event	2014 14th International Conference on Control, Automation and Systems, ICCAS 2014 - Gyeonggi-do, Korea, Republic of Duration: Oct 22 2014 → Oct 25 2014

Publication series

Name	International Conference on Control, Automation and Systems
ISSN (Print)	1598-7833

Other

Other	2014 14th International Conference on Control, Automation and Systems, ICCAS 2014
Country/Territory	Korea, Republic of
City	Gyeonggi-do
Period	10/22/14 → 10/25/14

Keywords

Bayesian statistical inference
compressed sensing
inverse halftoning

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICCAS.2014.6987771

Cite this

Sparse representation approach to inverse halftoning in terms of DCT dictionary. / Ohta, Yuhri; Aida, Toshiaki.
International Conference on Control, Automation and Systems. IEEE Computer Society, 2014. p. 1377-1380 6987771 (International Conference on Control, Automation and Systems).

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

Ohta, Y & Aida, T 2014, Sparse representation approach to inverse halftoning in terms of DCT dictionary. in International Conference on Control, Automation and Systems., 6987771, International Conference on Control, Automation and Systems, IEEE Computer Society, pp. 1377-1380, 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014, Gyeonggi-do, Korea, Republic of, 10/22/14. https://doi.org/10.1109/ICCAS.2014.6987771

@inproceedings{07cc2114340d4d0f987b8c475a4487ea,

title = "Sparse representation approach to inverse halftoning in terms of DCT dictionary",

abstract = "The problem of inverse halftoning is approached on the basis of compressed sensing, which enables us to make significantly efficient inference through the sparse representation of data to be inferred. For this purpose, we have adopted a DCT dictionary as a basis to represent image patches. In the Bayesian formulation of the problem taking the sparse representation into account, the MAP estimate is found to lead to an inverse halftoning algorithm which can be interpreted as a linear programming problem. Numerical simulations have successfully confirmed the effectiveness of the algorithm, which allows us to conclude that the compressed sensing approach is efficient to the problem of inverse halftoning.",

keywords = "Bayesian statistical inference, compressed sensing, inverse halftoning",

author = "Yuhri Ohta and Toshiaki Aida",

note = "Publisher Copyright: {\textcopyright} 2014 Institute of Control, Robotics and Systems (ICROS).; 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014 ; Conference date: 22-10-2014 Through 25-10-2014",

year = "2014",

month = dec,

day = "16",

doi = "10.1109/ICCAS.2014.6987771",

language = "English",

series = "International Conference on Control, Automation and Systems",

publisher = "IEEE Computer Society",

pages = "1377--1380",

booktitle = "International Conference on Control, Automation and Systems",

address = "United States",

}

TY - GEN

T1 - Sparse representation approach to inverse halftoning in terms of DCT dictionary

AU - Ohta, Yuhri

AU - Aida, Toshiaki

PY - 2014/12/16

Y1 - 2014/12/16

N2 - The problem of inverse halftoning is approached on the basis of compressed sensing, which enables us to make significantly efficient inference through the sparse representation of data to be inferred. For this purpose, we have adopted a DCT dictionary as a basis to represent image patches. In the Bayesian formulation of the problem taking the sparse representation into account, the MAP estimate is found to lead to an inverse halftoning algorithm which can be interpreted as a linear programming problem. Numerical simulations have successfully confirmed the effectiveness of the algorithm, which allows us to conclude that the compressed sensing approach is efficient to the problem of inverse halftoning.

AB - The problem of inverse halftoning is approached on the basis of compressed sensing, which enables us to make significantly efficient inference through the sparse representation of data to be inferred. For this purpose, we have adopted a DCT dictionary as a basis to represent image patches. In the Bayesian formulation of the problem taking the sparse representation into account, the MAP estimate is found to lead to an inverse halftoning algorithm which can be interpreted as a linear programming problem. Numerical simulations have successfully confirmed the effectiveness of the algorithm, which allows us to conclude that the compressed sensing approach is efficient to the problem of inverse halftoning.

KW - Bayesian statistical inference

KW - compressed sensing

KW - inverse halftoning

UR - http://www.scopus.com/inward/record.url?scp=84920177507&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84920177507&partnerID=8YFLogxK

U2 - 10.1109/ICCAS.2014.6987771

DO - 10.1109/ICCAS.2014.6987771

M3 - Conference contribution

AN - SCOPUS:84920177507

T3 - International Conference on Control, Automation and Systems

SP - 1377

EP - 1380

BT - International Conference on Control, Automation and Systems

PB - IEEE Computer Society

T2 - 2014 14th International Conference on Control, Automation and Systems, ICCAS 2014

Y2 - 22 October 2014 through 25 October 2014

ER -

Sparse representation approach to inverse halftoning in terms of DCT dictionary

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this