Compressive image sampling with side information

@article{Stankovi2009CompressiveIS,
  title={Compressive image sampling with side information},
  author={Vladimir Stankovi{\'c} and Lina Stankovi{\'c} and Samuel Cheng},
  journal={2009 16th IEEE International Conference on Image Processing (ICIP)},
  year={2009},
  pages={3037-3040}
}
Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this paper, we apply compressive sampling to reduce the sampling rate of images/video. The key idea is to exploit the intra- and inter-frame correlation to improve signal recovery algorithms. The image is split into non-overlapping blocks of fixed size, which are independently compressively sampled exploiting sparsity of natural scenes in the Discrete… CONTINUE READING

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