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논문검색

A Saliency Detection Method Based on Global Contrast

초록

영어

To highlight the saliency object clearly from the foreground, we propose a saliency detection method based on global contrast with cluster. Due to the fact that background pixels usually have similar patches, we use cluster analysis to merge the background regions. By using mean shift filter, the background pixels with similar color level are clustered and the saliency calculation can be decreased a lot. In the method, we use the contrast of color feature with all the other pixels to compute the saliency map. A weight coefficient is utilized to improve the detection accuracy in global contrast differences evaluation. The results of extensive experiments on public dataset show that our method perform well and can highlight the salient object clearly against the other five state-of-the-art methods. Besides, we demonstrate that the applications in image segmentation and fusion with our saliency map can get satisfactory results.

목차

Abstract
 1. Introduction
 2. HC Algorithm
 3. The Proposed Method
  3.1 Mean Shift Filter
  3.2 Saliency Map computation
 4. Experimental Results
 5. Applications
  5.1 Image Segmentation
  5.2 Image Fusion
 6. Conclusion
 Acknowledgments
 References

저자정보

  • Chun-yan Yu Institute of Information and Science Technology, Dalian Martiime University, Key Laboratory of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, No3. Feixi Road, Hefei
  • Wei-shi Zhang Institute of Information and Science Technology, Dalian Martiime University
  • Chun-li Wang Institute of Information and Science Technology, Dalian Martiime University

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