Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images

@article{Lohit2017ConvolutionalNN,
  title={Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images},
  author={Suhas Lohit and Kuldeep Kulkarni and Ronan Kerviche and Pavan K. Turaga and Amit Ashok},
  journal={IEEE Transactions on Computational Imaging},
  year={2017},
  volume={4},
  pages={326-340}
}
Traditional algorithms for compressive sensing recovery are computationally expensive and are ineffective at low measurement rates. In this paper, we propose a data-driven noniterative algorithm to overcome the shortcomings of earlier iterative algorithms. Our solution, ReconNet, is a deep neural network, which is learned end-to-end to map block-wise compressive measurements of the scene to the desired image blocks. Reconstruction of an image becomes a simple forward pass through the network… CONTINUE READING
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