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Image Enlargement Based on Low- to High-frequency Components Mapping Derived from Self-decomposed Images

  • Hideaki Kawano
  • Noriaki Suetake
  • Byungki Cha
  • Takashi Aso
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 4)

Due to the wide diffusion of multimedia applications and wide area screens-for example, video walls—the problem of image size conversion (especially image enlargement) has significantly increased in importance. Various image enlargement methods have been proposed so far [1], and they are split into multi-frame image enlargement methods and single-frame methods.

The multi-frame image enlargement is a process of combining multiple frames of low-resolution images in the same scene for the reconstruction of a single highresolution image. Many multi-frame image enlargement methods have been proposed up to now. For example, there are the frequency domain methods [2–4], the projection onto convex sets (POCS) methods [5, 6], and the maximum a posteriori (MAP) methods [7–9]. They can obtain good enlargement performance with respect to image quality. However, their computational complexity and storage consumption are tremendous. It is, therefore, very difficult to realize real-time processing by them.

Keywords

Support Vector Machine Little Square Support Vector Machine Synthetic Image Ideal Image Enlarge Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Hideaki Kawano
    • 1
  • Noriaki Suetake
    • 2
  • Byungki Cha
    • 3
  • Takashi Aso
    • 3
  1. 1.Kyushu Institute of TechnologyKyushu Institute of TechnologyJapan
  2. 2.Graduate School of Science and EngineeringYamaguchi UniversityJapan
  3. 3.Faculty of Management and Information SciencesKyushu Institute of Information SciencesJapan

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