원문정보
초록
영어
The block compressed sensing has brought forth the problem that the reconstructed image is of lower quality compared with that of the compressed sensing. A new method is proposed in this paper, named as Block Compressed Sensing of Self-adaptive Measurement and Combinatorial Optimization, which capably solves the problem. According to different sparsity of each image block, we firstly measure the blocks by using different projections; then, we choose measurement with the optimal reconstruction as the final measurement. Eventually, reconstruct the original image using the optimal measurement we got. The proposed method outperforms the compressed sensing in terms of real-time and better reconstruction quality is achieved than the block compressed sensing. Our experimental results verify the superiority of the proposed method.
목차
1. Introduction
2. Compressed Sensing
2.1. The Sparse Represent of Signal
2.2. Non-linear Optimization Reconstruction
2.3. The Irrelevant Measurement
3. AMCO-BCS
4. Experiments
4.1. Experimental Environment and Index
4.2. Experimental Procedure
5. Conclusions
Acknowledgements
References