A fast and robust map-based superresolution reconstruction method using cdhs and block-wise motion vector selection

Hsi Kuan Chen, Chin Hsing Chen, Shih Jen Wang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

High computational complexity and occlusion including the extreme case of a scene change, are, the two most, critical problems in super-resolution (SR) reconstruction. In this paper, we adopted the Cross-Diamond-Hexagonal Search (CDHS) block-matching algorithm (BMA) to reduce the complexity significantly. The CDHS BMA reduced about 2/3 computation time without sacrificing the reconstruction quality comparable to the full search BMA but it has high, noises, unqualified motion vectors, resulted, from occlusion existing in each frame of a sequence. We further proposed a simple and robust block-wise motion vector selection (BWMVS) strategy that can remove occlusion effectively. The stability due to BWMVS was verified by the reconstruction results using the interpolation methods (nearest, bilinear, and bicubic). The experimental results showed that by combining the CDHS BMA and BWMVS, high quality images in SR reconstruction can be obtained without complex computation. ICIC International

Original languageEnglish
Pages (from-to)3105-3120
Number of pages16
JournalInternational Journal of Innovative Computing, Information and Control
Volume6
Issue number7
Publication statusPublished - 2010 Jul 1

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computational Theory and Mathematics

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