IEEE Trans Image Process - Image reconstruction from double random projection.

Tópicos

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Resumo

We present double random projection methods for reconstruction of imaging data. The methods draw upon recent results in the random projection literature, particularly on low-rank matrix approximations, and the reconstruction algorithm has only two simple and noniterative steps, while the reconstruction error is close to the error of the optimal low-rank approximation by the truncated singular-value decomposition. We extend the often-required symmetric distributions of entries in a random-projection matrix to asymmetric distributions, which can be more easily implementable on imaging devices. Experimental results are provided on the subsampling of natural images and hyperspectral images, and on simulated compressible matrices. Comparisons with other random projection methods are also provided.

Resumo Limpo

present doubl random project method reconstruct imag data method draw upon recent result random project literatur particular lowrank matrix approxim reconstruct algorithm two simpl nonit step reconstruct error close error optim lowrank approxim truncat singularvalu decomposit extend oftenrequir symmetr distribut entri randomproject matrix asymmetr distribut can easili implement imag devic experiment result provid subsampl natur imag hyperspectr imag simul compress matric comparison random project method also provid

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