Research on image analysis and processing method based on compressed perception technology

[1] Cascianelli, S., Costante, G., Devo, A., Ciarfuglia, T. A., & Fravolini, M. L. (2019). The role of the input in natural language video description. IEEE Transactions on Multimedia, PP(99), 1-1. Search in Google Scholar

[2] Sepehr, S., & Head, M. (2018). Understanding the role of competition in video gameplay satisfaction. Information & Management, 55( 4), 407-421. Search in Google Scholar

[3] Macdonald, I. (2021). Window on the weather: a case study in multi-platform visual communication design, with a relationship to design thinking. Visual Communication, 22(2), 365-386. Search in Google Scholar

[4] Mei, J., & Moura, J. M. (2016). Signal processing on graphs: Causal modeling of unstructured data. IEEE Transactions on Signal Processing, 65(8), 2077-2092. Search in Google Scholar

[5] Cheng, S., Zhang, Z. Y., Zhou, F., Li, M., Chen, H., & Shi, F. S., et al. (2021). 3d step-by-step inversion strategy for audio magnetotellurics data based on unstructured mesh. Applied Geophysics, 18(3), 375-385. Search in Google Scholar

[6] Yuan, M., Gao, Y., Cavallaro, A., Parini, C. G., Wei, Z., & Liang, Y. C. (2017). Sparsity independent sub-nyquist rate wideband spectrum sensing on real-time tv white space. IEEE Transactions on Vehicular Technology, PP(10), 1-1. Search in Google Scholar

[7] Qi, X., Wu, N., Wang, H., & Yuan, W. (2017). A factor graph-based iterative detection of faster-than-nyquist signaling in the presence of phase noise and carrier frequency offset. Digital Signal Processing, 63, 25-34. Search in Google Scholar

[8] Liu, W, & Wang, Z. (2019). A novel multi-focus image fusion method using multiscale shearing nonlocal guided averaging filter. Signal Processing, 166, 107252. Search in Google Scholar

[9] Mota, J., Deligiannis, N., & Rodrigues, M. (2017). Compressed sensing with prior information: strategies, geometry, and bounds. IEEE Transactions on Information Theory, 63(7). Search in Google Scholar

[10] Wang, X., & Fu, F. W. (2017). Deterministic construction of compressed sensing matrices from codes. International Journal of Foundations of Computer Science, 28(02), 99-109. Search in Google Scholar

[11] Moench, S., Sollmann, N., Hock, A., Zimmer, C., Kirschke, J. S., & Hedderich, D. M. (2020). Magnetic resonance imaging of the brain using compressed sensing - quality assessment in daily clinical routine. Clinical neuroradiology.(2), 30. Search in Google Scholar

[12] Hu, Z., Zhao, C., Zhao, X., Kong, L., & Zhou, Y. (2021). Joint reconstruction framework of compressed sensing and nonlinear parallel imaging for dynamic cardiac magnetic resonance imaging. BMC Medical Imaging, 21(1). Search in Google Scholar

[13] Zhang, S., Wu, J., Chen, D., Li, S., & Qu, J. (2018). Fast frequency-domain compressed sensing analysis for high-density super-resolution imaging using orthogonal matching pursuit. IEEE Photonics Journal, PP(99), 1-1. Search in Google Scholar

[14] You, D., Zhang, J., Xie, J., Chen, B., & Ma, S. (2021). Coast: Controllable arbitrary-sampling network for compressive sensing. IEEE Transactions on Image Processing, 30, 6066-6080. Search in Google Scholar

[15] Zhu, Y., Liu, W., Shen, Q., Wu, Y., & Bao, H. (2020). Jpeg lifting algorithm based on adaptive block compressed sensing. Mathematical Problems in Engineering, 2020. Search in Google Scholar

[16] Qin, S. (2020). Simple algorithm for 1-norm regularisation-based compressed sensing and image restoration. IET Image Processing, 14(1). Search in Google Scholar

[17] Ren, S., Zhang, T., Wang, M., & Shahzad, K. (2020). Identifiable tampering multi-carrier image information hiding algorithm based on compressed sensing. IEEE Access, 8, 214992-215009. Search in Google Scholar

[18] Fan, Q., & Zhang, M. (2017). Image inpainting method based on compressed sensing. Revista de la Facultad de Ingenieria, 32(10), 412-417. Search in Google Scholar