Remote sensing image object extraction using convex geometric active contour model
Authors: 
Ning He, Lulu Zhang, Yixue WangAuthors Info & Claims
Ning He, Lulu Zhang, Yixue WangAuthors Info & ClaimsPages 203 - 206
Abstract
The geometric active contour model is a popular method for computing the segmentation of an image into two phases, based on Mumford-Shah model. The main problem in image segmentation based this method may lead to non-convex minimization problems that it difficult to obtain a global solution. In this paper, we propose a convex relaxation of the popular K-means algorithm. Our approach is based on the vector-valued relaxation technique developed by Brown et al. (UCLA CAM Report 10-43, 2010) and Goldstein et al. (UCLA CAM Report 09-77, 2009). We applied the proposed framework to multi-object extraction problems on remote sensing images. We provide several experimental results to demonstrate that our convex model yields global solutions to the well known Mumford-Shah model.
References
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Index Terms
- Remote sensing image object extraction using convex geometric active contour model
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Published In
August 2013
419 pages
ISBN:9781450322522
DOI:10.1145/2499788
- Conference Chair:
- Tat-Seng Chua,
- General Chairs:
- Ke Lu,
- Tao Mei,
- Xindong Wu
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Sponsors
- NSF of China: National Natural Science Foundation of China
- University of Sciences & Technology, Hefei: University of Sciences & Technology, Hefei
- Beijing ACM SIGMM Chapter
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 August 2013
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- Research-article
Funding Sources
- Foundation of Beijing Educational Committee
- The Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
Conference
ICIMCS '13
Sponsor:
- NSF of China
- University of Sciences & Technology, Hefei
ICIMCS '13: International Conference on Internet Multimedia Computing and Service
August 17 - 19, 2013
Huangshan, China
Acceptance Rates
ICIMCS '13 Paper Acceptance Rate 20 of 94 submissions, 21%;
Overall Acceptance Rate 163 of 456 submissions, 36%
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