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Reconstruction of probability density functions from channel representations
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Computer Vision.ORCID iD: 0000-0002-6096-3648
2005 (English)In: Scandinavian Conference on Image Analysis, 2005, Vol. 3540, 491-500 p.Conference paper, Published paper (Refereed)
Abstract [en]

The channel representation allows the construction of soft histograms, where peaks can be detected with a much higher accuracy than in regular hard-binned histograms. This is critical in e.g. reducing the number of bins of generalized Hough transform methods. When applying the maximum entropy method to the channel representation, a minimum-information reconstruction of the underlying continuous probability distribution is obtained. The maximum entropy reconstruction is compared to simpler linear methods in some simulated situations. Experimental results show that mode estimation of the maximum entropy reconstruction outperforms the linear methods in terms of quantization error and discrimination threshold. Finding the maximum entropy reconstruction is however computationally more expensive.

Place, publisher, year, edition, pages
2005. Vol. 3540, 491-500 p.
Series
Lecture Notes in Computer Science, 3540
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-48190OAI: oai:DiVA.org:liu-48190DiVA: diva2:269086
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2016-05-04

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Felsberg, Michael

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