Perception-Driven Resizing for Dynamic Image Sequences

Lingling Zi1,2, Junping Du1, Lisha Hou1, Xiangda Sun1 and Jangmyung Lee3

  1. Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications
    100876 Beijing, China
  2. School of Electronic and Information Engineering, Liaoning Technical University
    125105 Huludao, China
  3. Department of Electronics Engineering, Pusan National University
    Busan, Korea


With the development of multimedia display devices, dynamic image sequence resizing, which can adapt image sequences to be displayed on devices with different resolutions, is becoming more important. However, existing approaches do not resize results from the viewpoint of the user. In this paper, we present a new resizing framework, which uses the feature descriptor technique and the image interpolation technique, that aims to improve the resizing quality of the important content perceived by user. To accomplish this, we use a coarse-to-fine detection approach to determine the important content of image sequences, and construct a partition interpolation model to improve the definitions of important content. By adopting a region energy protection approach we can obtain high quality image displays. Compared to representative algorithms in image resizing, our method can achieve satisfactory performance not only in terms of image visualization but also in terms of quantitative measures.

Key words

image resizing, human visual perception, image Interpolation, feature descriptor, dynamic image sequence

Digital Object Identifier (DOI)

Publication information

Volume 10, Issue 3 (June 2013)
Year of Publication: 2013
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Zi, L., Du, J., Hou, L., Sun, X., Lee, J.: Perception-Driven Resizing for Dynamic Image Sequences. Computer Science and Information Systems, Vol. 10, No. 3, 1343-1357. (2013),