Practical background estimation for mosaic blending with patch-based Markov random fields
SCIE
SCOPUS
- Title
- Practical background estimation for mosaic blending with patch-based Markov random fields
- Authors
- Kim, DW; Hong, KS
- Date Issued
- 2008-07
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Abstract
- In this paper, we present a new background estimation algorithm which effectively represents both background and foreground. The problem is formulated with a labeling problem over a patch-based Markov random field (MRF) and solved with a graph-cuts algorithm. Our method is applied to the problem of mosaic blending considering the moving objects and exposure variations of rotating and zooming camera. Also, to reduce seams in the estimated boundaries, we propose a simple exposure correction algorithm using intensities near the estimated boundaries. (c) 2008 Published by Elsevier Ltd.
- Keywords
- background; mosaic; blending; GRAPH CUTS; ENERGY MINIMIZATION; IMAGE; TEXTURES
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/22764
- DOI
- 10.1016/j.patcog.2008.01.015
- ISSN
- 0031-3203
- Article Type
- Article
- Citation
- PATTERN RECOGNITION, vol. 41, no. 7, page. 2145 - 2155, 2008-07
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- There are no files associated with this item.
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