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- W2361337368 abstract "A novel algorithm for hyperspectral image(HSI) denoising which is based on the tensor subspace is proposed.Considering the HSI as 3 order tensor data,this approach introduces a data representation involving multi-dimensional processing and projects such data into the signal subspace by tensor subspace decomposition.The optimization criterion used in this algorithm is the minimization of mean square error between the estimated signal and the desired signal,then the alternating projection algorithm is adopted to determine the optimal filter in each dimension.Comparative studies with conventional denoising methods such as 2D Wiener filtering and channel-by-channel wavelet thresholding show that our algorithm provides better performance using AVIRIS and PHI datasets." @default.
- W2361337368 created "2016-06-24" @default.
- W2361337368 creator A5066135984 @default.
- W2361337368 date "2013-01-01" @default.
- W2361337368 modified "2023-09-23" @default.
- W2361337368 title "Tensor Subspace Based Multiway Filtering Algorithm for Hyperspectral Images" @default.
- W2361337368 hasPublicationYear "2013" @default.
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