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Color Edge Saliency Boosting Using Natural Image Statistics

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Titel Color Edge Saliency Boosting Using Natural Image Statistics
Serientitel The 5th European Conference on Colour in Graphics, Imaging, and Vision and the 12th International Symposium on Multispectral Colour Science (CGIV 2010/MCS'10)
Teil 17
Anzahl der Teile 43
Autor Vigo, David Rojas
Weijer, Joost van de
Gevers, Theo
Lizenz CC-Namensnennung - keine Bearbeitung 2.0 UK: England & Wales:
Sie dürfen das Werk in unveränderter Form zu jedem legalen Zweck nutzen, vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen.
DOI 10.5446/18251
Herausgeber River Valley TV
Erscheinungsjahr 2011
Sprache Englisch
Produktionsort Joensuu, Finland

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Fachgebiet Informatik
Abstract State of the art methods for image matching, content-based retrieval and recognition use local features. Most of these still exploit only the luminance information for detection. The color saliency boosting algorithm has provided an efficient method to exploit the saliency of color edges based on information theory. However, during the design of this algorithm, some issues were not addressed in depth: (1) The method has ignored the underlying distribution of derivatives in natural images. (2) The dependence of information content in color-boosted edges on its spatial derivatives has not been quantitatively established. (3) To evaluate luminance and color contributions to saliency of edges, a parameter gradually balancing both contributions is required. We introduce a novel algorithm, based on the principles of independent component analysis, which models the first order derivatives of color natural images by a generalized Gaussian distribution. Furthermore, using this probability model we show that for images with a Laplacian distribution, which is a particular case of generalized Gaussian distribution, the magnitudes of color-boosted edges reflect their corresponding information content. In order to evaluate the impact of color edge saliency in real world applications, we introduce an extension of the Laplacian-of-Gaussian detector to color, and the performance for image matching is evaluated. Our experiments show that our approach provides more discriminative regions in comparison with the original detector.
Schlagwörter The 5th European Conference on Colour in Graphics, Imaging
Vision and the 12th International Symposium on Multispectral Colour Science

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