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Author Maria Vanrell; Jordi Vitria; Xavier Roca edit  openurl
  Title A multidimensional scaling approach to explore the behavior of a texture perception algorithm. Type Journal Article
  Year 1997 Publication Machine Vision and Applications Abbreviated Journal  
  Volume 9 Issue Pages 262–271  
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  Notes (down) OR;ISE;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VVR1997 Serial 35  
Permanent link to this record
 
 
Author Mikhail Mozerov; Joost Van de Weijer edit   pdf
doi  openurl
  Title Improved Recursive Geodesic Distance Computation for Edge Preserving Filter Type Journal Article
  Year 2017 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 26 Issue 8 Pages 3696 - 3706  
  Keywords Geodesic distance filter; color image filtering; image enhancement  
  Abstract All known recursive filters based on the geodesic distance affinity are realized by two 1D recursions applied in two orthogonal directions of the image plane. The 2D extension of the filter is not valid and has theoretically drawbacks, which lead to known artifacts. In this paper, a maximum influence propagation method is proposed to approximate the 2D extension for the
geodesic distance-based recursive filter. The method allows to partially overcome the drawbacks of the 1D recursion approach. We show that our improved recursion better approximates the true geodesic distance filter, and the application of this improved filter for image denoising outperforms the existing recursive implementation of the geodesic distance. As an application,
we consider a geodesic distance-based filter for image denoising.
Experimental evaluation of our denoising method demonstrates comparable and for several test images better results, than stateof-the-art approaches, while our algorithm is considerably fasterwith computational complexity O(8P).		  
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  Notes (down) LAMP; ISE; 600.120; 600.098; 600.119 Approved no  
  Call Number Admin @ si @ Moz2017 Serial 2921  
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Author Mikhail Mozerov; Joost Van de Weijer edit  doi
openurl 
  Title Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering Type Journal Article
  Year 2015 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 24 Issue 12 Pages 5842-5853  
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  Abstract The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results.  
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  ISSN 1057-7149 ISBN Medium  
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  Notes (down) LAMP; 600.079;ISE Approved no  
  Call Number Admin @ si @ MoW2015b Serial 2689  
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Author Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich edit  doi
openurl 
  Title Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception Type Journal Article
  Year 2010 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
  Volume 27 Issue 3 Pages 613–621  
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  Abstract In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%.  
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  Notes (down) ISE;CIC Approved no  
  Call Number CAT @ cat @ VGL2010 Serial 1275  
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Author Arjan Gijsenji; Theo Gevers; Joost Van de Weijer edit   pdf
url  doi
openurl 
  Title Computational Color Constancy: Survey and Experiments Type Journal Article
  Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 20 Issue 9 Pages 2475-2489  
  Keywords computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting  
  Abstract Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets.  
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  ISSN 1057-7149 ISBN Medium  
  Area Expedition Conference  
  Notes (down) ISE;CIC Approved no  
  Call Number Admin @ si @ GGW2011 Serial 1717  
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