Edge-oriented two-step interpolation based on training set

Ji Hoon Lee, Jong Ok Kim, Jong Woo Han, Kang Sun Choi, Sung Jea Ko

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Preserving the sharpness of edge structures is highly challenging to image interpolation. In this paper, we propose an edge-oriented two-step interpolation method that utilizes an edge training set. For edge interpolation, the LR edge map is converted into the HR edge map by using the training set. Then, an image is classified into smooth and edge regions using the HR edge map, and both regions are interpolated separately. For edge regions, adaptive edgeoriented interpolation is performed by using the detailed edge structures learned from training. The proposed method is extensively evaluated, and its performance is compared with the conventional edge-based methods. Experimental results show that the proposed method can not only reconstruct the missed edge information by the training set, but also significantly reduce blurring and jagging artifacts around edges by separately interpolating smooth and edge regions.

Original languageEnglish
Article number5606336
Pages (from-to)1848-1855
Number of pages8
JournalIEEE Transactions on Consumer Electronics
Issue number3
Publication statusPublished - 2010 Aug

Bibliographical note

Funding Information:
1 This research was supported by a Korea University Grant. J.-H. Lee, J.-O. Kim, J.-W. Han, K.-S. Choi, and S.-J. Ko are with School of Electrical Engineering, Korea University in Seoul 136-713, Korea (e-mail: jokim@ korea.ac.kr).


  • Edge Map
  • Edge-Oriented
  • Image Interpolation
  • Training Set

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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