• DocumentCode
    20934
  • Title

    Salient Region Detection Using Patch Level and Region Level Image Abstractions

  • Author

    Kannan, Ravindran ; Ghinea, Gheorghita ; Swaminathan, Sridhar

  • Author_Institution
    Coll. of Comput. Sci. & Inf. Technol., King Faisal Univ., Al Ahsa, Saudi Arabia
  • Volume
    22
  • Issue
    6
  • fYear
    2015
  • fDate
    Jun-15
  • Firstpage
    686
  • Lastpage
    690
  • Abstract
    In this letter, a novel salient region detection approach is proposed. Firstly, color contrast cue and color distribution cue are computed by exploiting patch level and region level image abstractions in a unified way, where these two cues are fused to compute an initial saliency map. A simple and computationally efficient adaptive saliency refinement approach is applied to suppress saliency of background noises, and to emphasize saliency of objects uniformly. Finally, the saliency map is computed by integrating the refined saliency map with center prior map. In order to compensate different needs in speed/accuracy tradeoff, three variants of the proposed approach are also presented in this letter. The experimental results on a large image dataset show that the proposed approach achieve the best performance over several state-of-the-art approaches.
  • Keywords
    image colour analysis; object detection; adaptive saliency refinement approach; color contrast cue; color distribution cue; novel salient region detection approach; patch level image abstractions; region level image abstractions; Educational institutions; Estimation; Image color analysis; Image segmentation; Materials; Noise measurement; Robustness; Adaptive saliency refinement; center prior; color contrast; color distribution; saliency detection;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2014.2366192
  • Filename
    6942143