4.6 Article

Registration of Images With Outliers Using Joint Saliency Map

期刊

IEEE SIGNAL PROCESSING LETTERS
卷 17, 期 1, 页码 91-94

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2009.2033728

关键词

Image registration; joint saliency map; mutual information; outliers; weighted joint histogram

资金

  1. NSFC [60872102]
  2. NBRPC [2010CB834303]
  3. Science Foundation of Shanghai Municipal Science & Technology Commission [04JC14060]
  4. Shanghai Municipal Health Bureau [2008115]
  5. Small Animal Imaging Project [06-545]

向作者/读者索取更多资源

Mutual information (MI) is a popular similarity measure for image registration, whereby good registration can be achieved by maximizing the compactness of the clusters in the joint histogram. However, MI is sensitive to the outlier objects that appear in one image but not the other, and also suffers from local and biased maxima. We propose a novel joint saliency map (JSM) to highlight the corresponding salient structures in the two images, and emphatically group those salient structures into the smoothed compact clusters in the weighted joint histogram. This strategy could solve both the outlier and the local maxima problems. Experimental results show that the JSM-MI based algorithm is not only accurate but also robust for registration of challenging image pairs with outliers.

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