• Laser & Optoelectronics Progress
  • Vol. 57, Issue 16, 161506 (2020)
Guoliang Yang, Dingling Yu*, and Zhendong Lai
Author Affiliations
  • School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China
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    DOI: 10.3788/LOP57.161506 Cite this Article Set citation alerts
    Guoliang Yang, Dingling Yu, Zhendong Lai. Video Denoising and Object Detection Based on RPCA Model with l1-TV Regularization Constraints[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161506 Copy Citation Text show less
    References

    [1] Wang H Q, Xu T F, Sun X L et al. Infrared-visible video registration with matching motion trajectories of targets[J]. Optics and Precision Engineering, 26, 1533-1541(2018).

    [2] Chen Z C, Wu X L, Zhao F J. Denoising and implementation of photoplethysmography signal based on EEMD and wavelet threshold[J]. Optics and Precision Engineering, 27, 1327-1334(2019).

    [3] WrightJ, GaneshA, RaoS, et al.Robust principal component analysis: exact recovery of corrupted low-rank matrices by convex optimization[C]∥Proceedings of Neural Information Processing Systems. Whistler: MIT Press, 2009: 2080- 2088.

    [4] Guyon C, Bouwmans T, Zahzah E H. Foreground detection based on low-rank and block-sparse matrix decomposition. [C]∥2012 19th IEEE International Conference on Image Processing, September 30-October 3, 2012. Orlando, FL, USA. IEEE, 1225-1228(2012).

    [5] Shahid N, Kalofolias V, Bresson X et al. Robust principal component analysis on graphs. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015. Santiago, Chile. IEEE, 2812-2820(2015).

    [6] Zhou X W, Yang C, Yu W C. Moving object detection by detecting contiguous outliers in the low-rank representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 597-610(2013).

    [7] Cao X C, Yang L, Guo X J. Total variation regularized RPCA for irregularly moving object detection under dynamic background[J]. IEEE Transactions on Cybernetics, 46, 1014-1027(2016).

    [8] Liu X, Zhao G Y, Yao J W et al. Background subtraction based on low-rank and structured sparse decomposition[J]. IEEE Transactions on Image Processing, 24, 2502-2514(2015).

    [9] Javed S, Mahmood A, Bouwmans T et al. Background-foreground modeling based on spatiotemporal sparse subspace clustering[J]. IEEE Transactions on Image Processing, 26, 5840-5854(2017).

    [10] Shijila B, Tom A J, George S N. Moving object detection by low rank approximation and l1-TV regularization on RPCA framework[J]. Journal of Visual Communication and Image Representation, 56, 188-200(2018).

    [11] Lang H, Ding S, Lu J et al. Traffic video significance foreground target extraction in complex scenes[J]. Journal of Image and Graphics, 24, 50-63(2019).

    [12] Javed S, Bouwmans T, Jung S K. Stochastic decomposition into low rank and sparse tensor for robust background subtraction. [C]∥6th International Conference on Imaging for Crime Prevention and Detection (ICDP-15), London, UK. Institution of Engineering and Technology, 5-7(2015).

    [13] Chen L X, Liu Y P, Zhu C. Iterative block tensor singular value thresholding for extraction of lowrank component of image data. [C]∥2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), March 5-9, 2017. New Orleans, LA. IEEE, 1862-1866(2017).

    [14] Barbero Á. -12-30)[2019-11-01]. https:∥arxiv., org/abs/1411, 0589(2017).

    Guoliang Yang, Dingling Yu, Zhendong Lai. Video Denoising and Object Detection Based on RPCA Model with l1-TV Regularization Constraints[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161506
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