Enhanced Tensor RPCA and Its Application.

IEEE Transactions on Pattern Analysis and Machine Intelligence(2021)

引用 89|浏览150
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摘要
Despite the promising results, tensor robust principal component analysis (TRPCA), which aims to recover underlying low-rank structure of clean tensor data corrupted with noise/outliers by shrinking all singular values equally, cannot well preserve the salient content of image. The major reason is that, in real applications, there is a salient difference information between all singular values of ...
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关键词
Tensors,Minimization,Image color analysis,Principal component analysis,Periodic structures,Sparse matrices,Linear programming
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