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 journalArticlepeer-review

16 Citations (Scopus)


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 languageEnglish
Article number5955199
Pages (from-to)615-622
Number of pages8
JournalIEEE Transactions on Consumer Electronics
Issue number2
Publication statusPublished - 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} Y. Joo is with Samsung Electronics, Suwon, Republic of Korea.


  • Fourier analysis
  • Image and video retargeting
  • Lagrangian multiplier technique
  • salience map

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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