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Image Decomposition and Texture Segmentation via Sparse Representation
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DOI：10.1109/LSP.2008.2002722.png)
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摘要
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Decomposing an image into a texture part and a nontexture (cartoon) part, as well as grouping the texture part into several homogeneous subparts, is studied in this letter. The so-called texture part is composed of both the self-similar structure and the oscillatory noise. The self-similar structure of each homogenous subtexture is captured in its principal subspace. Both the segmentation and the decomposition are essentially related to sparse representation and are united to a framework.
Keyword:
Clustering
principal component analysis (PCA)
sparse representation
texture
total variation
unsupervised learning
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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