Content-aware image and video resizing based on frequency domain analysis

Jun Seong Kim; Seong Gyun Jeong; Younghun Joo; Chang-Su Kim

doi:10.1109/TCE.2011.5955199

Content-aware image and video resizing based on frequency domain analysis

Jun Seong Kim, Seong Gyun Jeong, Younghun Joo, Chang-Su Kim

Research output: Contribution to journal › Article › peer-review

18 Citations (Scopus)

Abstract

An adaptive image and video resizing algorithm based on the frequency domain analysis is proposed in this work. Given an image, we first construct an importance map by combining the gradient and the saliency information. We partition the image into several strips so that each strip contains pixels of similar importance levels. We model the distortion, which is caused by scaling a strip, in the frequency domain. Then, we scale each strip adaptively to minimize the overall distortion of the whole image. Moreover, we extend the proposed algorithm for video resizing. We add the motion term to construct the importance map, and suppress excessive parameter variations to achieve jitter-free video resizing. Simulation results show that the proposed algorithm provides higher quality resizing results than conventional algorithms, although it requires lower computational complexity.

Original language	English
Article number	5955199
Pages (from-to)	615-622
Number of pages	8
Journal	IEEE Transactions on Consumer Electronics
Volume	57
Issue number	2
DOIs	https://doi.org/10.1109/TCE.2011.5955199
Publication status	Published - 2011 May

Bibliographical note

Funding Information:
Preliminary results of this work were partly presented in [1]. This work was supported partly by Samsung Electronics, partly by Seoul R&BD Program (No. ST090818), and partly by a Korea University Grant. J.–S. Kim, S.–G. Jeong, and C.–S. Kim are with the School of Electric Engineering, Korea University, Seoul, Republic of Korea, 136-713 (e-mails: {junssi153, sg_jeong, changsukim}@korea.ac.kr). Y. Joo is with Samsung Electronics, Suwon, Republic of Korea.

Keywords

Fourier analysis
Image and video retargeting
Lagrangian multiplier technique
salience map

ASJC Scopus subject areas

Media Technology
Electrical and Electronic Engineering

Access to Document

10.1109/TCE.2011.5955199

Cite this

@article{5077d8e718654c63892d1e1de87082ed,

title = "Content-aware image and video resizing based on frequency domain analysis",

abstract = "An adaptive image and video resizing algorithm based on the frequency domain analysis is proposed in this work. Given an image, we first construct an importance map by combining the gradient and the saliency information. We partition the image into several strips so that each strip contains pixels of similar importance levels. We model the distortion, which is caused by scaling a strip, in the frequency domain. Then, we scale each strip adaptively to minimize the overall distortion of the whole image. Moreover, we extend the proposed algorithm for video resizing. We add the motion term to construct the importance map, and suppress excessive parameter variations to achieve jitter-free video resizing. Simulation results show that the proposed algorithm provides higher quality resizing results than conventional algorithms, although it requires lower computational complexity.",

keywords = "Fourier analysis, Image and video retargeting, Lagrangian multiplier technique, salience map",

author = "Kim, {Jun Seong} and Jeong, {Seong Gyun} and Younghun Joo and Chang-Su Kim",

note = "Funding Information: Preliminary results of this work were partly presented in [1]. This work was supported partly by Samsung Electronics, partly by Seoul R&BD Program (No. ST090818), and partly by a Korea University Grant. J.–S. Kim, S.–G. Jeong, and C.–S. Kim are with the School of Electric Engineering, Korea University, Seoul, Republic of Korea, 136-713 (e-mails: {junssi153, sg_jeong, changsukim}@korea.ac.kr). Y. Joo is with Samsung Electronics, Suwon, Republic of Korea.",

year = "2011",

month = may,

doi = "10.1109/TCE.2011.5955199",

language = "English",

volume = "57",

pages = "615--622",

journal = "IEEE Transactions on Consumer Electronics",

issn = "0098-3063",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "2",

}

TY - JOUR

T1 - Content-aware image and video resizing based on frequency domain analysis

AU - Kim, Jun Seong

AU - Jeong, Seong Gyun

AU - Joo, Younghun

AU - Kim, Chang-Su

N1 - Funding Information: Preliminary results of this work were partly presented in [1]. This work was supported partly by Samsung Electronics, partly by Seoul R&BD Program (No. ST090818), and partly by a Korea University Grant. J.–S. Kim, S.–G. Jeong, and C.–S. Kim are with the School of Electric Engineering, Korea University, Seoul, Republic of Korea, 136-713 (e-mails: {junssi153, sg_jeong, changsukim}@korea.ac.kr). Y. Joo is with Samsung Electronics, Suwon, Republic of Korea.

PY - 2011/5

Y1 - 2011/5

N2 - An adaptive image and video resizing algorithm based on the frequency domain analysis is proposed in this work. Given an image, we first construct an importance map by combining the gradient and the saliency information. We partition the image into several strips so that each strip contains pixels of similar importance levels. We model the distortion, which is caused by scaling a strip, in the frequency domain. Then, we scale each strip adaptively to minimize the overall distortion of the whole image. Moreover, we extend the proposed algorithm for video resizing. We add the motion term to construct the importance map, and suppress excessive parameter variations to achieve jitter-free video resizing. Simulation results show that the proposed algorithm provides higher quality resizing results than conventional algorithms, although it requires lower computational complexity.

AB - An adaptive image and video resizing algorithm based on the frequency domain analysis is proposed in this work. Given an image, we first construct an importance map by combining the gradient and the saliency information. We partition the image into several strips so that each strip contains pixels of similar importance levels. We model the distortion, which is caused by scaling a strip, in the frequency domain. Then, we scale each strip adaptively to minimize the overall distortion of the whole image. Moreover, we extend the proposed algorithm for video resizing. We add the motion term to construct the importance map, and suppress excessive parameter variations to achieve jitter-free video resizing. Simulation results show that the proposed algorithm provides higher quality resizing results than conventional algorithms, although it requires lower computational complexity.

KW - Fourier analysis

KW - Image and video retargeting

KW - Lagrangian multiplier technique

KW - salience map

UR - http://www.scopus.com/inward/record.url?scp=79960928989&partnerID=8YFLogxK

U2 - 10.1109/TCE.2011.5955199

DO - 10.1109/TCE.2011.5955199

M3 - Article

AN - SCOPUS:79960928989

SN - 0098-3063

VL - 57

SP - 615

EP - 622

JO - IEEE Transactions on Consumer Electronics

JF - IEEE Transactions on Consumer Electronics

IS - 2

M1 - 5955199

ER -

Content-aware image and video resizing based on frequency domain analysis

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this