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231224s2014 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2014.2307475
|2 doi
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|a eng
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| 100 |
1 |
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|a McCann, Michael T
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Images as occlusions of textures
|b a framework for segmentation
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|c 2014
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 29.09.2015
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| 500 |
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|a Date Revised 08.04.2014
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|a published: Print
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|a Citation Status MEDLINE
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| 520 |
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|a We propose a new mathematical and algorithmic framework for unsupervised image segmentation, which is a critical step in a wide variety of image processing applications. We have found that most existing segmentation methods are not successful on histopathology images, which prompted us to investigate segmentation of a broader class of images, namely those without clear edges between the regions to be segmented. We model these images as occlusions of random images, which we call textures, and show that local histograms are a useful tool for segmenting them. Based on our theoretical results, we describe a flexible segmentation framework that draws on existing work on nonnegative matrix factorization and image deconvolution. Results on synthetic texture mosaics and real histology images show the promise of the method
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
1 |
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|a Mixon, Dustin G
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Fickus, Matthew C
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Castro, Carlos A
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ozolek, John A
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Kovacevic, Jelena
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 23(2014), 5 vom: 07. Mai, Seite 2033-46
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|x 1941-0042
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| 773 |
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|g volume:23
|g year:2014
|g number:5
|g day:07
|g month:05
|g pages:2033-46
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|u http://dx.doi.org/10.1109/TIP.2014.2307475
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