Hypergraph-based saliency map generation with potential region-of-interest approximation and validation

Z. Liang, H. Fu, Zheru Chi, D.D. Feng

Research output: Journal article publicationJournal articleAcademic researchpeer-review


A novel saliency model is proposed in this paper to automatically process images in the similar way as the human visual system which focuses on conspicuous regions that catch human beings’ attention. The model combines a hypergraph representation and a partitioning process with potential region-of-interest (p-ROI) approximation and validation. Experimental results demonstrate that the proposed method shows considerable improvement in the performance of saliency map generation.
Original languageEnglish
Pages (from-to)1-4
Number of pages4
JournalJournal of Electronic Imaging
Issue number1
Publication statusPublished - Jan 2012


  • Approximation theory
  • Graph theory
  • Image representation

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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