• Infrared and Laser Engineering
  • Vol. 51, Issue 3, 20210468 (2022)
Bing Xie1, Shuhui Wan1, and Yunhua Yin2、3
Author Affiliations
  • 1Department of Network Security, Henan Police College, Zhengzhou 450046, China
  • 2School of Electronics and Control Engineering, North University of China, Taiyuan 030051, China
  • 3Science and Technology on Transient Impact Laboratory, Beijing 102202, China
  • show less
    DOI: 10.3788/IRLA20210468 Cite this Article
    Bing Xie, Shuhui Wan, Yunhua Yin. SR reconstruction algorithm of regularization based on improve of sparse representation[J]. Infrared and Laser Engineering, 2022, 51(3): 20210468 Copy Citation Text show less
    References

    [1] Chengming Jiang, Jinhui Song. An ultrahigh-resolution digital image sensor with pixel size of 50 nm by vertical nanorod arrays. Advanced Materials, 27, 4454-4460(2015).

    [2] Xiu Zhang, Wei Zhou. Image super-resolution reconstruction based on convolution sparse self-encoding. Infrared and Laser Engineering, 48, 0126005(2019).

    [3] Zhihong Xi, Caiyan Hou, Kunpeng Yuan, et al. Accelerated image super-resolution reconstruction based on deep residual network. Acta Optica Sinica, 89-98(2019).

    [4] Siu WanChi, Hung KwokWai. Review of image interpolation superresolution[C]AsiaPacific Signal Infmation Processing Association Annual Summit Conference, 2012.

    [5] R Fernandez-Beltran, P Latorre-Carmona, F Pla. Single-frame super-resolution in remote sensing: A practical overview. International Journal of Remote Sensing, 38, 314-354(2017).

    [6] Bertero M, Boccacci P. Introduction to Inverse Problems Imaging[M]. Bristol: Institute of Physics Publishing, 1998: 18.

    [7] Zhao X Q, Jia Y X. An adaptive regularization image superresolution reconstruction algithm[C]2014 33rd Chinese Control Conference (CCC). IEEE, 2014.

    [8] Q Cai, Y D Liu, J Cao, et al. A watershed image segmentation algorithm based on self-adaptive marking and interregional affinity propagation clustering. Acta Electronica Sinica, 45, 1911-1918(2017).

    [9] L Jing, S Liu, L Zhihong, et al. An image reconstruction algorithm based on the extended Tikhonov regularization method for electrical capacitance tomography. Measurement, 42, 368-376(2009).

    [10] Shuiping Gou, Shuzhen Liu, Yaosheng Wu, et al. Image super-resolution based on the pairwise dictionary selected learning and improved bilateral regularization. IET Image Processing, 10, 101-112(2016).

    [11] E S Lee, M G Kang. Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration. IEEE Transactions on Image Processing, 12, 826-37(2003).

    [12] Yubing Han, Lenan Wu, Dongqing Zhang. Super-resolution reconstruction based on regularization processing. Journal of Electronics & Information Technology, 29, 1713-1716(2007).

    [13] A Marquina, S J Osher. Image super-resolution by TV-regularization and Bregman iteration. Journal of Scientific Computing, 37, 367-382(2008).

    [14] Omer O A, Tanaka T. Regionbased weightednm approach to video superresolution with adaptive regularization[C] IEEE International Conference on Acoustics, 2009: 833836.

    [15] J P Oliveira, J M BioucasDias, M A Figueiredo. Adaptive total variation image deblurring: A majorization-minimization approach.. Signal Processing, 89, 1683-1693(2009).

    [16] D L Donoho. De-noising by soft-thresholding. IEEE Transactions on Information Theory, 41, 613-627(1995).

    [17] Emmanuel J Candès, M B Wakin, S P Boyd. Enhancing sparsity by reweighted l1 minimization. Journal of Fourier Analysis & Applications, 14, 877-905(2008).

    [18] Jia C, Evans B L. Patchbased image deconvolution via joint modeling of sparse pris[C]IEEE International Conference on Image Processing, 2011: 681684.

    [19] W Dong, L Zhang, G Shi, et al. Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization. IEEE Transactions on Image Processing, 20, 1838-1857(2011).

    [20] Leigh Donoho David. Compressed sensing. IEEE Transactions on Information Theory, 52, 1289-1306(2006).

    [21] Julien Mairal. Incremental majorization-minimization optimization with application to large-scale machine learning. SIAM Journal on Optimization, 25, 829-855(2015).

    [22] Papa G, Bianchi P, Clémençon S. Adaptive sampling f incremental optimization using stochastic gradient descent[C]International Conference on Algithmic Learning They, 2015.

    Bing Xie, Shuhui Wan, Yunhua Yin. SR reconstruction algorithm of regularization based on improve of sparse representation[J]. Infrared and Laser Engineering, 2022, 51(3): 20210468
    Download Citation