Compressive Sensing SAR Image Reconstruction Based on Bayesian Framework and Evolutionary Computation

@article{Wu2011CompressiveSS,
  title={Compressive Sensing SAR Image Reconstruction Based on Bayesian Framework and Evolutionary Computation},
  author={Jiao Wu and Fang Liu and Licheng Jiao and Xiaodong Wang},
  journal={IEEE Transactions on Image Processing},
  year={2011},
  volume={20},
  pages={1904-1911}
}
Compressive sensing (CS) is a theory that one may achieve an exact signal reconstruction from sufficient CS measurements taken from a sparse signal. However, in practical applications, the transform coefficients of SAR images usually have weak sparsity. Exactly reconstructing these images is very challenging. A new Bayesian evolutionary pursuit algorithm (BEPA) is proposed in this paper. A signal is represented as the sum of a main signal and some residual signals, and the generalized Gaussian… CONTINUE READING
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