An Optimization Method of Deterministic Measurement Matrix in Distributed Compressed Video Sensing
Jiawei Qin, Dengyin Zhang, Liang Xie
Available Online March 2018.
- https://doi.org/10.2991/iceea-18.2018.38How to use a DOI?
- compressed sensing; orthogonal symmetric toeplitz matrix (OSTM); pseudorandom
- This electronic Compressed Sensing (CS) is a new theoretical framework for information acquisition and processing, which provides a new way for signal sampling. In order to solve the problem of the constraints of traditional Nyquist sampling theorem, CS based on the sparsity of signal, randomness of the measurement matrix and nonlinear optimization algorithm can achieve the compression and reconstruction of the signal. In the process of compressive sensing, the measurement matrix plays an important role in signal sampling and reconstruction. This construction is based on the orthogonal symmetric Toeplitz matrix in this paper. The pseudorandom feature of the deterministic measurement matrix is improved by pseudorandom loop construction method to ensure the random performance of the measurement matrix and optimize the compression measurement effect.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jiawei Qin AU - Dengyin Zhang AU - Liang Xie PY - 2018/03 DA - 2018/03 TI - An Optimization Method of Deterministic Measurement Matrix in Distributed Compressed Video Sensing BT - 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018) PB - Atlantis Press SP - 176 EP - 179 SN - 2352-5401 UR - https://doi.org/10.2991/iceea-18.2018.38 DO - https://doi.org/10.2991/iceea-18.2018.38 ID - Qin2018/03 ER -