Semi-Supervised subspace learning for Mumford-Shah model based texture segmentation
نویسندگان
چکیده
منابع مشابه
Subspace learning for Mumford-Shah-model-based texture segmentation through texture patches.
In this paper, we develop a robust and effective algorithm for texture segmentation and feature selection. The approach is to incorporate a patch-based subspace learning technique into the subspace Mumford-Shah (SMS) model to make the minimization of the SMS model robust and accurate. The proposed method is fully unsupervised in that it removes the need to specify training data, which is requir...
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Recently, the Subspace Mumford-Shah (SMS) model has been proposed for simultaneous texture segmentation and feature selection. The optimal segmentation and features are obtained via solving a joint minimization problem. Due to the non-convexity of the objective function, the computation of a solution is non-trivial and even more difficult than standard Mumford-Shah-type problems. Various ways t...
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ژورنال
عنوان ژورنال: Optics Express
سال: 2010
ISSN: 1094-4087
DOI: 10.1364/oe.18.004434