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Author (up) Miguel Oliveira; Angel Sappa; V. Santos edit   pdf
doi  isbn
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  Title Color Correction using 3D Gaussian Mixture Models Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7324 Issue I Pages 97-106  
  Keywords  
  Abstract The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.  
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  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 10.1007/978-3-642-31295-3_12 Medium  
  Area Expedition Conference ICIAR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OSS2012a Serial 2015  
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