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Laser & Optoelectronics Progress, Volume. 56, Issue 3, 031005(2019)

Multi-Scale Block Adaptive Sampling Rate Compression Sensing Algorithm

Deqiang Cheng1、*, Lirong Shao1, Yan Li1, and Zenglun Guan2
Author Affiliations
  • 1 School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China
  • 2 China Coal Energy Group Co. Ltd., Beijing 100120, China
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    References(14)

    [1] Wang M, Liu K X, Liu L et al. Super-resolution reconstruction of image based on optimized convolution neural network[J]. Laser & Optoelectronics Progress, 54, 111005(2017).

    [2] Chen J, Gao H B, Wang W G et al. Methods and applications of image super-resolution restoration[J]. Laser & Optoelectronics Progress, 52, 020004(2015).

    [3] Zhang L, Yang J F, Xue B et al. Modified MAP algorithm for single frame super-resolution reconstruction[J]. Laser & Optoelectronics Progress, 48, 011003(2011).

    [4] Tang C Y, Chen Y T, Li Q et al. Adaptive temporal compressive sensing for video based on signal correlation[J]. Acta Optica Sinica, 36, 1010001(2016).

    [5] Weng J W, Yang C P, Li H. Self-interference incoherent digital holography by compressive sensing[J]. Acta Optica Sinica, 36, 0209001(2016).

    [6] Tang J L, Chen Z B, Su B H et al. Super-resolution restoration of low quality face images[J]. Laser & Optoelectronics Progress, 55, 031007(2018).

    [7] Gan L. Blockcompressed sensing of natural images. [C]∥15th International Conference on Digital Signal Processing, 403-406(2007).

    [8] Li R, Zhu X C. A PCA-based smoothed projected Landweber algorithm for block compressed sensing image reconstruction. [C]∥2012 International Conference on Image Analysis and Signal Processing, 1-6(2012).

    [9] Jiang Y W, Yu X M. An image variable sampling and reconstruction algorithm based DWT multiscale block compressed sensing[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 52, 30-33(2013).

    [10] Gao D H. The image processing algorithm research based on multiscale block compressed sensing[D]. Beijing: Beijing Institute of Technology(2016).

    [11] Li Y, Zhao R Z, Zhang F Z et al. Adaptive multi-scale block compressed sensing algorithm based on edge and direction estimation[J]. Signal Processing, 31, 407-413(2015).

    [12] Antonini M, Barlaud M, Mathieu P et al. Image coding using wavelet transform[J]. IEEE Transactions on Image Processing, 1, 205-220(1992). http://europepmc.org/abstract/MED/18296155

    [13] Zhang X Q, Gu X D, Sun H X. Deblock algorithm for compressed image based on adaptive space domain filtering[J]. Computer Engineering, 35, 218-220(2009).

    [14] Piana M, Bertero M. Projected Landweber method and preconditioning[J]. Inverse Problems, 13, 441-463(1997). http://www.ingentaconnect.com/content/iop/ip/1997/00000013/00000002/art00016

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    Deqiang Cheng, Lirong Shao, Yan Li, Zenglun Guan. Multi-Scale Block Adaptive Sampling Rate Compression Sensing Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(3): 031005

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    Paper Information

    Category: Image Processing

    Received: Jun. 6, 2018

    Accepted: Aug. 31, 2018

    Published Online: Jul. 31, 2019

    The Author Email: Deqiang Cheng (m15162143261@163.com)

    DOI:10.3788/LOP56.031005

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology