Image Texture Balancing in the Wavelet Domain Based on a Ripple Matrix Permutation

Author:

Du Xiuli,Liu Jinting,Zhang Wei,Lv Ya’na

Publisher

Springer Singapore

Reference12 articles.

1. Seong, J.-t.: Review on non-iterative recovery frameworks in compressed sensing. In: ICEIC 2018: 2018 International Conference on Electronics, Information, and Communication, vol. 5, no. 5, pp. 1–2 (2018).

2. Sun, L., Fan, Z., Fu, X., et al.: A deep information sharing network for multi-contrast compressed sensing MRI reconstruction. IEEE Trans. Image Process. 28(12), 6141–6153 (2019)

3. Cui, H., Zhang, S., Gan, H. et al.: Information recovery via block compressed sensing in wireless sensor networks. In: ICC: IEEE International Conference on Communications, vol. 7, no. 14, pp. 1–6 (2016)

4. Chen, P., Guodong, Y., Xiaoling, H., et al.: Novel meaningful image encryption based on block compressive sensing. Secur. Commun. Netw. 2019, 6572105 (2019)

5. Pimentel-Romero, C.H., Mangia, M., Pareschi, F., et al.: Geometric constraints in sensing matrix design for compressed sensing. Signal Process. 171, 107498. (2020). UNSP

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