DSMM

• Officical code of paper "Deep Neural Network based Sparse Measurement Matirx for Image Compressed Sensing" ICIP2018
• Download the paper: https://arxiv.org/pdf/1806.07026v1.pdf

Framework of DSMM

Requirements

• Windows10
• Matlab R2015b
• MatconvNet 1.0-beta23 (https://www.vlfeat.org/matconvnet/)
• CUDA 8.0

How to Run

Training

• Generating the imdb training data for DSMM by running GenerateData_DSMM.m
• Train the DSMM, run the code Demo_Train_DSMM.m

Matrix_Sparse.m is used for sparse constraint and Matirx_orth.m is used for norm constraint.

Testing

• Obtain the learned measurement matrix from the trained model by running get_sampling_mat.m
• Using the learned measurement matrix to replace the traditional gaussian matrix for different iteration based CS methods.

Experimental Results

• Subjective results

• Objective results

Additional instructions

• For training data, you can choose any dataset by yourself.
• If you like this repo, Star or Fork to support my work. Thank you.
• If you have any problem, please email wxcui@hit.edu.cn

Citation

• If you find the code is useful in your research, please cite:

@article{Cui2018An,
  title={Deep Neural Network based Sparse Measurement Matirx for Image Compressed Sensing},
  journal={IEEE International Conference on Image Processing (ICIP)},
  author={Cui, Wenxue, Jiang, Feng, Gao, Xinwei, Tao, Wen and Zhao, Debin},
  year={2018},
}

Acknowledgments

This code is built based on the repo https://github.com/cszn/DnCNN